Hyunsun A. Kim

Emerging evidence implicates organelle dysfunction, particularly within peroxisomes, as a critical driver of hair follicle degeneration and alopecia. While mitochondrial defects are well characterized in the context of hair loss, the contribution of peroxisomal failure to follicular homeostasis remains largely unexplored. Here, we identify peroxisomal dysfunction as a central molecular and metabolic defect underlying hair follicle aging and loss. Comprehensive transcriptomic analysis of human dermal papilla cells from alopecia patients revealed marked downregulation of peroxisome-associated pathways, including fatty acid β-oxidation, lipid degradation, and detoxification of reactive oxygen species. These alterations were recapitulated in Nudt7 -deficient mice, in which targeted disruption of peroxisomal lipid metabolism leads to pronounced hair thinning, follicle miniaturization, and exacerbated oxidative stress. To therapeutically address peroxisomal impairment, we developed catalytic nanozymes (HA-Hem) that mimic peroxisomal catalase activity. Nanozyme treatment restored metabolic balance, reduced oxidative damage, and stimulated hair follicle regeneration in both wild-type and immunodeficient murine models. Mechanistically, nanozymes increased PPARα expression, thereby enhancing peroxisomal biogenesis and lipid metabolism. Elevated PPARα further improved peroxisome and mitochondrial function and strengthened peroxisome–mitochondria interactions, resulting in coordinated restoration of cellular redox and metabolic homeostasis. Compared with minoxidil treatment, nanozyme therapy produced greater regenerative responses and maintained therapeutic efficacy in immunodeficient settings. Spatial transcriptomic analysis further demonstrated an increased expression of keratin-associated proteins and cytoskeletal genes, consistent with activation of regenerative programs. These findings support a metabolism-focused therapeutic strategy targeting peroxisomal function in the treatment of alopecia.

The design of specified nonlinear mechanical responses into a structure or material is a highly sought after capability, with significant potential impacts in areas such as wave tailoring in metamaterials, impact mitigation, soft robotics, and biomedicine. Here, we present a topology optimization approach to design two-dimensional structures for desired uniaxial polynomial nonlinear behavior, wherein we formulate the objective function to match nonlinear coefficient ratios, such that the linear stiffness is decoupled from the desired nonlinearity of the response. We suggest that such linear stiffness decoupling can help aid convergence for problems with fixed, but poorly matched, constituent materials and design volumes. This benefit can be understood by considering, if large absolute force values and stiffnesses are targeted, thicker structures with less open space generally result. Such high volume ratio structures reduce the kinematic freedom (available to, e.g. , long thin structures) which is needed for strong geometrically nonlinear responses. We show designs achieved using this approach that match a range of qualitatively different polynomial behaviors with high precision, which are of interest, in particular, within the domain of dynamical systems where nonlinear elasticity of relatively simple polynomial forms can confer greater analytical tractability.

Size and shape optimisation has long been studied to maximise the critical buckling load whilst reducing the mass of stiffened panels used extensively in the structures and aerospace sectors. Moving into the postbuckling regime, where this is stable, provides the opportunity to further reduce weight and material usage, increasingly important in decarbonisation and the achievement of net zero. This study introduces topology optimization for the postbuckling of stiffened panels. A level set-based topology optimization parameterization, previously applied to linear buckling optimization, is extended to postbuckling optimization. The thicknesses of both the skin and stiffeners, stiffener layout and internal topologies are simultaneously optimized. Stiffened panels under force loading are considered for optimization. The Newton-Raphson scheme with load control is used for postbuckling analysis, where a small imperfection in the form of the first linear buckling mode is imposed on the finite element model. Two possibilities are explored – maximising load-carrying capacity and minimising out-of-plane skin deformation. Sensitivity information is shown, and a gradient-based optimizer is used to solve the optimization problems. A numerical example is used to demonstrate the application of the proposed method to postbuckling optimization of stiffened panels and highlight differences from linear buckling optimization.

Size and shape optimization has long been studied to maximize the critical buckling load whilst reducing the mass of stiffened panels used extensively in the structures and aerospace sectors. Moving into the postbuckling regime, where this is stable, provides the opportunity to further reduce weight and material usage, increasingly important in decarbonisation and the achievement of net zero. With the opportunities further extended by the use of topology optimisation and novel manufacturing techniques such as additive manufacturing we are no longer limited to prismatic stiffened panel structures, further expanding the design space for lightweight structures. This study introduces topology optimization for the postbuckling of stiffened panels. A level-set based topology optimization parameterization, which has been successfully applied to linear buckling optimization, is extended to postbuckling optimization. The thicknesses of both the skin and stiffeners, as well as the stiffener layout and internal topologies are simultaneously optimized. Stiffened panels under force loading are considered for optimization. The Newton-Raphson scheme with load control is used for postbuckling analysis, where a small imperfection in the form of the first linear buckling mode is imposed on the finite element model. Two possibilities are explored – maximizing load-carrying capacity and minimizing out-of-plane skin deformation. Two optimization formulations, respectively considering these two postbuckling metrics are studied. Sensitivity information is shown, and a gradient-based optimizer is used to solve the optimization problems. A numerical example is used to demonstrate the application of the proposed method to postbuckling optimization of stiffened panels and highlight differences from linear buckling optimization.

Eigenvalue problems play a fundamental role in structural dynamics and engineering design, with topology optimization offering powerful tools for achieving superior performance. While most research has focused on eigenvalue maximization, only a few studies have explored eigenvalue assignment or reduction. This work investigates the challenges associated with eigenfrequency minimization in level-set topology optimization, highlighting the risk of infeasible or fragmented designs. To overcome these issues, we propose a formulation that integrates connectivity constraints to preserve structural integrity, thereby addressing an inherent limitation of eigenfrequency reduction. A comparative analysis of eigenfrequency minimization and maximization is presented, emphasizing the role of the ersatz material interpolation scheme and the impact of constraint enforcement. The proposed methodology is demonstrated through numerical examples, illustrating its effectiveness in achieving feasible layouts and highlighting its potential applications across a wide class of structural dynamics problems.

Passive wave transformation via nonlinearity is ubiquitous in settings from acoustics to optics and electromagnetics. It is well known that different nonlinearities yield different effects on propagating signals, which raises the question of "what precise nonlinearity is the best for a given wave tailoring application?" In this work, considering a one-dimensional spring-mass chain connected by polynomial springs (a variant of the Fermi-Pasta-Ulam-Tsingou system), we introduce a bilevel inverse design method which couples the shape optimization of structures for tailored constitutive responses with reduced-order nonlinear dynamical inverse design. We apply it to two qualitatively distinct problems-minimization of peak transmitted kinetic energy from impact, and pulse shape transformation-demonstrating our method's breadth of applicability. For the impact problem, we obtain two fundamental insights. First, small differences in nonlinearity can drastically change the dynamic response of the system, from severely under- to outperforming a comparative linear system. Second, the oft-used strategy of impact mitigation via "energy locking" bistability can be significantly outperformed by our optimal nonlinearity. We validate this case with impact experiments and find excellent agreement. This study establishes a framework for broader passive nonlinear mechanical wave tailoring material design, with applications to computing, signal processing, shock mitigation, and autonomous materials.

본 연구에서는 GFRP 보강근 콘크리트 슬래브-기둥 접합부의 뚫림전단강도를 분석하기 위하여, 슬래브의 주인장보강근비와 기둥 크기를 변수로 하는 3개의 실험체에 대하여 뚫림전단실험을 수행하였다. 실험결과 GFRP 보강근비가 증가할수록 실험체의 최대강도가 증가하고, 위험단면길이가 감소할 경우 처짐과 최대강도가 감소함을 확인하였다. 또한 실험에서 관측된 결과를 바탕으로 균열 패턴 및 변형률 등을 분석하였다. ACI.440.11-22, JSCE, CSA의 현행 이방향 뚫림전단강도식은 모두 실험체의 뚫림전단강도를 과소평가하고 있으며, 따라서 슬래브의 GFRP 보강근비와 기둥 크기 등 주요 변수에 따른 강도 변화를 정확하게 반영하기 위해 개선이 필요한 것으로 나타났다.

The practical application of all-solid-state batteries (ASSBs) requires reliable operation at low pressures, which remains a significant challenge. In this work, we examine the role of a cathode composite microstructure composed of solid-state electrolyte (SSE) with different particle sizes. A composite made of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) and fine-particle Li 6 PS 5 Cl (LPSC) shows a more uniform distribution of SSE on the surface of NCM811 particles, ensuring intimate contact. Moreover, the composite features reduced tortuosity, which enhances Li ion conduction. These microstructural advantages result in significantly reduced charge transfer resistance, helping to suppress mechanical distortion and electrochemical degradation during cycling under low-pressure conditions. As a result, the fine-LPSC cathode composite exhibits enhanced cycling stability at a moderate stack pressure of 2 MPa, outperforming its coarse-LPSC counterpart. Our finding confirms the important role of microstructure design in enabling high-performance ASSBs operating under low-pressure conditions.

Large-scale gradient-based Multidisciplinary Design Optimization (MDO) can aid in the exploration of high-dimensional design spaces for novel air vehicle concepts, thereby leading to more efficient and economic designs. This paper builds on past works where we demonstrated large-scale physics-based MDO capabilities and applied these to NASA's lift-plus-cruise electric air taxi concept. We extend this comprehensive mid-fidelity system-level optimization problem with high(er)-fidelity subsystem-level optimizations of various aircraft systems and mission phases, with the aim of further enhancing the accuracy and scope of the aforementioned system-level optimization problem: 1) Power minimization during the transition mission phase; 2) Electrical powertrain topology optimization; 3) Cell chemistry modeling and thermo-mechanical battery pack topology optimization; 4) Shell-based coupled aero-elastic wing structure optimization. An Analytical Target Cascading-like distributed MDO architecture allows us to couple the system- and subsystem-level optimizations in order to arrive at a consistent and feasible design. We find that the system-level design is most heavily impacted by the reduced battery pack-level energy densities that stem from power peaks in the mission profile. These power peaks seem to result from the inefficient lift rotor blade designs that are needed to satisfy noise constraints. We draw conclusions based on trends in our results and give recommendations for future MDO studies of electrical air taxi vehicle concepts.

Developing electric aircraft presents significant technical challenges, including the need for thermal management to control battery temperature and prevent catastrophic failures caused by thermal runaway. During battery discharge, heat is generated, which can lead to high temperatures and potential safety hazards. Phase-change materials (PCM) offer a potential solution by providing a high latent heat capacity, allowing them to store significant thermal energy during phase transitions. This characteristic helps slow down temperature rise and mitigate sudden temperature spikes. However, PCM's low thermal conductivity poses a challenge, necessitating the integration of materials with higher thermal conductivity to enhance heat transfer. In this study, we use the level-set method to optimize the distribution of PCM and high thermal conductivity materials within an electric aircraft battery pack. We model the heat transfer process as an unsteady diffusion problem, incorporating PCM through the apparent heat capacity method. Using the finite element method, implemented with FEniCS, we solve for the temperature distribution at each time-step. Given the power requirements of an electric aircraft, heat generation from the batteries is predicted using the Doyle-Fuller-Newman model, a physics-based electrochemical model implemented using PyBaMM. The optimization problem is solved with ParaLeSTO, an in-house topology optimization software written in C++ with a Python interface. Power requirements for the batteries are determined for different potential electric aircraft flights and high-energy density lithium-ion batteries, which are promising for electric aircraft, are used for the analysis. The study compares optimized designs incorporating PCM with reference designs with only PCM or only high thermal conductivity materials. This research aims to advance battery pack design using PCM for electric aircraft, contributing to improved thermal management in aerospace components and addressing key challenges in the industry.

Batteries are essential in various applications, including Electric Vertical Take-Off and Landing (eVTOL) vehicles, where performance, efficiency, and safety are paramount. However, the effects of battery shape and design on thermal management and overall efficiency remain underexplored. In this study, we present a computational framework for shape optimization of lithium-ion batteries with a focus on maximizing energy density. In this work, we model the battery electrochemistry using the Doyle Fuller Newman model, which has a homogenized domain of electrode active particles. In contrast to the common finite volume model, we develop a multiscale finite element model . The results are validated against the well-established finite volume solutions and then used to maximize energy storage and minimize ohmic losses using the level set topology optimization method. The sensitivities are obtained using the discrete adjoint method. To reduce the computational cost of the sensitivity calculations, we use a semi-symbolic approach to calculate the partial derivatives necessary for the adjoint method. A numerical optimization study indicates that optimizing the separator shape, between the anode and the cathode, can improve the energy performance by at least 43%.

In this paper, we describe research on the battery pack disassembly automation system necessary for recycling waste batteries generated due to the increase in electric vehicles. In particular, it describes the recognition process among the steps required to remove the cover of the battery pack during the automated disassembly process. The recognition process includes recognizing the battery pack through a global camera and recognizing the bolt through a local camera attached to each manipulator. In other words, the approximate location information of the bolt is obtained through the battery pack recognition process, and the exact location of the bolt is obtained using the manipulator's local camera to release the bolt. In the battery pack recognition process, the position and posture of the battery pack were estimated by matching point cloud data through the ICP(Iterative Closet Point) algorithm. The bolt recognition process was learned using the yolo v5 model, and the recognition rate was increased by classifying and tagging misrecognized objects into different classes.

Pectobacterium is a major bacterial causal agent leading to soft rot disease in host plants. With the Arabidopsis-Pectobacterium pathosystem, we investigated the function of an Arabidopsis thaliana WRKY55 during defense responses to Pectobacterium carotovorum ssp. carotovorum (Pcc). Pcc-infection specifically induced WRKY55 gene expression. The overexpression of WRKY55 was resistant to the Pcc infection, while wrky55 knockout plants compromised the defense responses against Pcc. WRKY55 expression was mediated via Arabidopsis COI1-dependent signaling pathway showing that WRKY55 can contribute to the gene expression of jasmonic acid-mediated defense marker genes such as PDF1.2 and LOX2. WRKY55 physically interacts with Arabidopsis ORA59 facilitating the expression of PDF1.2</i. Our results suggest that WRKY55 can function as a positive regulator for resistance against Pcc in Arabidopsis.

Topology optimization is an engineering design methodology that optimizes designs by manipulating material distribution. Level-set topology optimization (LSTO), a boundary-based method, has gained popularity for its crisp description of the design and natural handling of the topological changes during the optimization. However, its availability in commercial or open-source software is limited, and the entry barrier to LSTO could be considered high. This paper presents a workflow that seamlessly integrates LSTO with COMSOL Multiphysics, enabling broader accessibility. The workflow utilizes COMSOL’s versatile finite element solver to create models via their graphical user interface, which are then converted into MATLAB code. The LSTO modules, written in C++ for efficiency, are imported within MATLAB, adding topology optimization to the automatically generated COMSOL finite element code. The workflow leverages COMSOL’s adjoint sensitivity capabilities for efficient sensitivity computations during optimization. Three open-source examples showcasing the workflow’s effectiveness are provided, demonstrating heat conduction, fluid flow, and conjugate heat transfer optimization problems, and highlighting the power and versatility of the proposed approach.

Passive transformation of waves via nonlinear systems is ubiquitous in settings ranging from acoustics to optics and electromagnetics. Passivity is of particular importance for responding rapidly to stimuli and nonlinearity enormously expands signal transformability compared to linear systems due to the breaking of superposition. It is well known that different types of nonlinearity yield vastly different effects on propagating signals, which raises the question of ``what precise nonlinearity is the best for a given wave tailoring application?'' Considering a one-dimensional spring-mass chain as a testbed, we couple the shape optimization of structures for tailored nonlinear constitutive responses with reduced-order nonlinear dynamical inverse design. Using minimization of peak kinetic energy transmission from impact as a case study, we identify ideal nonlinear constitutive responses and the geometries needed to achieve them. As part of this, we show the large sensitivity of this metric to small changes in nonlinearity, and thus the need for high precision, free-form nonlinearity tailoring. We validate our predictions using impact experiments in a chain of nonlinear springs and masses. This work sets the foundation for broader passive nonlinear mechanical wave tailoring material design, with applications to computing, signal processing, shock mitigation, and autonomous materials.

Electric Vertical Take-Off and Landing (eVTOL) vehicles are considered a promising solution to alleviate traffic congestion and provide an alternative to traditional individual transportation. The design and performance of eVTOL battery packs play a critical role in the development of this mode of transportation. In this paper, we propose a methodology to topologically optimize an eVTOL battery pack using the level-set topology optimization method while considering multiphysics loading conditions. The objective is to obtain a thermally and structurally efficient lightweight structure. At the system level, a linear elastic beam model is developed to model the boom where the battery pack is located and obtain the mechanical load carried by the battery pack due to its placement in the vehicle. At the battery scale, a physics-based electrochemical model is applied to predict the maximum heat generation of the batteries due to the power requirements from a given mission profile. The mechanical load from the system scale and the thermal load from the battery scale are considered inputs for the battery pack thermo-mechanical model used for optimization.

Topology optimization is applied to design a lunar rover chassis to reduce thermal losses while maintaining adequate structural strength and stiffness. Space missions in extreme cold environments, such as the permanently shadowed regions (PSR) of the moon, are designed to reduce the power needed to maintain the minimum temperature for items that cannot operate at very low temperatures, such as electronic components. Energy consumed to maintain the temperature reduces the energy that could be used to operate instruments for improved science return. Consequently, it is essential to have an efficient thermal design while preserving the integrity of the structure. Given the design freedom it offers, topology optimization is an ideal candidate for such a task. In this work, the design of a rover chassis for extreme cold environments is investigated. The chassis is topologically optimized using the level-set method and moments-based meshfree finite element analysis with thermo-mechanical loads while the mass of the chassis is constrained to obtain a lightweight design. The main advantage of moment-based meshfree simulation is that it eliminates meshing-related bottlenecks, especially for large-scale multiphysics topology optimization problems. The objective function is defined as the weighted sum of thermal compliance and structural compliance. Several sets of weights are explored and the optimized designs are compared. The proposed methodology is reusable and extensible making it well-suited for a variety of designs for future space missions in extreme environments. The simulation and optimization tools that are developed in this study are available as a part of the software package, Intact.Generative from Intact Solutions.

Psoriasis is a chronic inflammatory skin disease characterized by epidermal hyperproliferation, aberrant differentiation of keratinocytes, and dysregulated immune responses. WW domain-containing oxidoreductase (WWOX) is a non-classical tumor suppressor gene that regulates multiple cellular processes, including proliferation, apoptosis, and migration. This study aimed to explore the possible role of WWOX in the pathogenesis of psoriasis. Immunohistochemical analysis showed that the expression of WWOX was increased in epidermal keratinocytes of both human psoriatic lesions and imiquimod-induced mice psoriatic model. Immortalized human epidermal keratinocytes were transduced with a recombinant adenovirus expressing microRNA specific for WWOX to downregulate its expression. Inflammatory responses were detected using Western blotting, real-time quantitative reverse transcription polymerase chain reaction (PCR), and enzyme-linked immunosorbent assay. In human epidermal keratinocytes, WWOX knockdown reduced nuclear factor-kappa B signaling and levels of proinflammatory cytokines induced by polyinosinic: polycytidylic acid [(poly(I:C)] in vitro. Furthermore, calcium chelator and protein kinase C (PKC) inhibitors significantly reduced poly(I:C)-induced inflammatory reactions. WWOX plays a role in the inflammatory reaction of epidermal keratinocytes by regulating calcium and PKC signaling. Targeting WWOX could be a novel therapeutic approach for psoriasis in the future.

BACKGROUND: Pyruvate kinase (PK) deficiency is a rare enzyme-linked glycolytic defect resulting in mild-to-severe chronic persistent erythrocyte hemolysis. The disease is an autosomal recessive trait caused by mutations in the PK liver and red blood cell gene characterized by insufficient erythrocyte PK activity. PK deficiency is most diagnosed in persons of northern European descent and managed with packed red blood cell transfusions, chelation, and splenectomy with cholecystectomy. Mitapivat is the first approved therapy indicated for hemolytic anemia in adults with PK deficiency with the potential for delaying splenectomy in mild-moderate disease. MECHANISM OF ACTION, PHARMACODYNAMICS, AND PHARMACOKINETICS: Mitapivat is a PK activator that acts by allosterically binding to the PK tetramer and increases PK activity. The red blood cell form of PK is mutated in PK deficiency, which leads to reduced adenosine triphosphate, shortened red blood cell lifespan, and chronic hemolysis. The half-life of elimination is 3-5 hours, with 73% bioavailability, 98% plasma protein binding, and a median duration of response of 7 months. CLINICAL TRIALS: Mitapivat has been investigated through various clinical trials for different therapeutic indications. Pivotal trials that serve the primary focus throughout this article are ACTIVATE, ACTIVATE-T, and RISE. ACTIVATE is a phase 3, randomized, double-blind, placebo-controlled study that evaluated the efficacy and safety of mitapivat in adult patients who were not receiving regular blood transfusions. Contrarily, ACTIVATE-T explored the safety and efficacy of mitapivat in adults with PK deficiency who received regular blood transfusions. Both trials demonstrated favorable use of mitapivat in PK deficiency. Focusing on another indication, the ongoing RISE trial investigates the optimal dosage of mitapivat in sickle cell disease. THERAPEUTIC ADVANCE: Mitapivat is an appropriate treatment for adults with PK deficiency requiring transfusions and may be considered for patients with symptomatic anemia who do not require transfusions and/or PK deficiency with compensated hemolysis without overt anemia.

A persistent challenge with the development of electric vertical take-off and landing vehicles (eVTOL) to meet flight power and energy demands is the mass of the load and thermal management systems for batteries. One possible strategy to overcome this problem is to employ optimization techniques to obtain a lightweight battery pack while satisfying structural and thermal requirements. In this work, a structural battery pack with high-energy-density cylindrical cells is optimized using the level-set topology optimization method. The heat generated by the batteries is predicted using a high-fidelity electrochemical model for a given eVTOL flight profile. The worst-case scenario for the battery's heat generation is then considered as a source term in the weakly coupled steady-state thermomechanical finite element model used for optimization. The objective of the optimization problem is to minimize the weighted sum of thermal compliance and structural compliance subjected to a volume constraint. The methodology is demonstrated with numerical examples for different sets of weights. The optimized results due to different weights are compared, discussed, and evaluated with thermal and structural performance indicators. The optimized pack topologies are subjected to a transient thermal finite element analysis to assess the battery pack's thermal response.

Abstract While products get more challenging to repair, the right-to-repair movement aims to empower consumers in their ability to “use, modify, and repair” a device “whenever, wherever, and however” they want. Here, the best design practices and remaining challenges of three industrial sectors – namely, consumer electronics, biomedical devices, and clothing industry – are investigated in light of the right-to-repair movement. Based on literature reviews and industrial surveys, a SWOT analysis is provided for each sector, and sustainable implications for product repair readiness are drawn. Concretely, recommendations to design, develop and sell products with right-to-repair in mind are given by sector. Future directions for a more quantitative assessment and implementation of design for product repair are discussed to ensure the augmentation of the circularity and sustainability performance of products.

Abstract Most manufacturing processes are inevitably characterized by process tolerances that ultimately affect the way a component behaves and complies with the design requirements. These uncertainties determine the real performance of a structure, with their impact growing with increasing deviations from the nominal values. This work introduces a simple approach, applicable to both static and dynamic cases, to conduct robust structural topology optimization in presence of manufacturing uncertainties. This approach, based on the level set method, makes use of a computationally efficient boundary-perturbation technique to describe over- and under-etching errors. Compared to the existing methods, it does not require a frequent re-initialization of the level set function, nor does it require a mapping between the etched structures and the nominal one. Moreover, compared to the standard case with uniform uncertainty, the technique presented in this work allows dealing with arbitrary spatially varying errors without increasing the computational cost.

This paper introduces the design, modeling, manufacturing, and testing of a Gripping Aerial Topology Optimized Robot (GATOR). The airframe of this unmanned aerial vehicle (UAV) is designed to be lightweight, structurally stiff, modular, and multi-functional. A Level-Set Topology Optimization (LSTO) method defines the external geometry of the frame, while the frame infill is controlled using a variable thickness latticing technique based on Finite Element Analysis (FEA) results. The UAV incorporates a soft robotic gripper, allowing the vehicle to collect delicate samples from the environment and perch for low-power use for extended periods. The bio-inspired design and fabrication of a mountable soft robotic gripper are presented and the associated kinematics are derived for controls. To further decrease the weight of the designs a novel volume-changing material was introduced following careful characterization through Scanning Electron Microscopy (SEM) and tensile testing. The resulting platform leverages additive manufacturing using material extrusion technology and can be swiftly instrumented with propulsion and flight control systems. The presented modular design methodology can be applied to the rapid prototyping of a broad range of aerial platforms and lightweight structures.

View Video Presentation: https://doi.org/10.2514/6.2023-0146.vid This paper presents a framework under development for enabling large-scale multi-fidelity modeling and optimization of electric vertical takeoff and landing concepts (eVTOL). The key features of the framework are a geometry-centric approach to multidisciplinary design optimization (MDO), a modular functional-form representation of the disciplines involved in aircraft design, and fully automated derivative computations thereby allowing efficient gradient-based optimization. The framework is first presented in a general manner agnostic to the vehicle concept or the physics-based analyses used. The key disciplines involved in the design of eVTOL aircraft and the couplings between the disciplines are described. The complex multidisciplinary nature of the design is emphasized. The framework is then applied to the design of the NASA lift-plus-cruise concept. Low-fidelity solvers of aerodynamics, propulsion, structural estimation, acoustics, powertrain, and battery are coupled together. The optimization considers 108 design variables and 16 constraints. It is shown that MDO considering geometric variables results in a design with lower gross mass than when the geometric variables are not considered. The optimization turnaround time of 30 minutes on a standard workstation demonstrates the capabilities of fully-coupled large-scale MDO using gradient-based optimization. The framework is under development and an open-source version will be released in the near-future.

View Video Presentation: https://doi.org/10.2514/6.2023-1675.vid This work is aimed at developing a workflow to use state-of-the-art level-set topology optimization (LSTO) methods with COMSOL Multiphysics. The graphical user interface (GUI) and solver of COMSOL Multiphysics are used to simplify the implementation of the considered physics problem. A physics model file (.m file) is then extracted from COMSOL Multiphysics, which can be called from and adjusted in MATLAB to make an interface with the level-set module. The LSTO modules written in C++ are imported into MATLAB to interface with the physics model extracted from COMSOL Multiphysics. The element sensitivities are computed in COMSOL Multiphysics and combined with the boundary perturbation method to calculate the boundary point (or shape) sensitivities using the discrete adjoint method. The capabilities of the proposed workflow are demonstrated with numerical examples. The proposed workflow alleviates the difficulty of implementing LSTO, especially in the case of coupled multiphysics problems.

View Video Presentation: https://doi.org/10.2514/6.2023-1270.vid This study introduces topology optimization for postbuckling of stiffened panels. A level-set-based topology optimization parameterization, which has been successfully applied to linear buckling optimization, is extended to postbuckling optimization of stiffened panels. The thicknesses of the skin and stiffeners, as well as the stiffener layout and internal topologies can be simultaneously optimized. Stiffened panels under force loading are considered for optimization. The Newton-Raphson scheme with load control is used for postbuckling analysis, where a small imperfection in the form of the first linear buckling mode is imposed on the finite element model. The out-of-plane skin deformation and load-carrying capability are considered to assess the postbuckling behaviors of stiffened panels. Two optimization formulations, respectively considering these two postbuckling metrics are studied. Sensitivity information is shown, and a gradient-based optimizer is used to solve the optimization problems. A numerical example is used to demonstrate the application of the proposed method to postbuckling optimization of stiffened panels and highlight differences from linear buckling optimization.

View Video Presentation: https://doi.org/10.2514/6.2023-2038.vid An efficient robust topology optimization under material uncertainty combined with the multifidelity Monte-Carlo method is presented in this study. One challenge associated with the Monte-Carlo method is often the prohibitive computational cost, as it usually requires the numerous samples of random variables to estimate statistics. To save the computational cost, we employ the multifidelity Monte-Carlo method which combines multiple cheap-to-evaluate low-fidelity models together with an expensive-to-evaluate single high-fidelity model. For the inverse design, the density-based topology optimization method is adopted and the sensitivities are computed by the adjoint variable method. Several numerical examples demonstrate the multifidelity design approach, and the results show that it can optimally allocate resources to the different fidelity models for a given budget as well as achieve a significant speed-up compared to the robust topology optimization based on the regular Monte-Carlo method for the same level of accuracy.