26 papers · ranked by Valyu relevance
Yang Liu, Wei Tan
Differential equation-driven evolution strategies are often associated with boundary-driven topology optimization methods, such as the level set method. However, differential equations can also be utilized effectively in density-based approaches. This paper presents a design update scheme formulated using differential…
Jyotiranjan nayak, Shafeequdheen P, Vijayakrishna Rowthu
This study investigates the impact of finite element selection on structural topology optimization using the SIMP (Solid Isotropic Material with Penalization) method. Specifically, it compares linear (P1) and quadratic (P2) triangular elements with the conventional bi-linear quadrilateral (Q1) elements. Numerical…
Binhe Chen, Yaodan Chen, Li Cao, Changzu Chen + 3 more
The Crested Porcupine Optimizer (CPO), as a newly emerging swarm intelligence algorithm, demonstrates advantages in balancing global exploration and local exploitation but still suffers from limitations in convergence speed and local exploitation precision. To address these issues, this paper proposes an enhanced…
João Sartori, Eduardo Krempser, Ana Carolina Ramos Guimarães, Lucas de Almeida Machado
The optimization of protein sequences for enhanced binding and stability remains a formidable challenge in bioengineering due to the vastness of sequence space. Existing state-of-the-art methods, including traditional structure-based design and protein language models, use fitness estimators as objective functions to…
Igor Rodríguez, Maria Laura Santoni, Fabian Duddeck, Carola Doerr + 2 more
Benchmarking is essential for developing and evaluating black-box optimization algorithms, providing a structured means to analyze their search behavior. Its effectiveness relies on carefully selected problem sets used for evaluation. To date, most established benchmark suites for black-box optimization consist of…
Burak Kaymak, Heming Jia
This study presents an optimization tool inspired by bone remodeling principles to address the high computational costs of truss topology optimization. Additionally, a new structural analysis method based on primary forces is proposed to overcome the kinematic stability problem. The strategy developed to obtain the…
Minchao Fang, Chentong Wang, Jungang Shi, Fengbai Lian + 10 more
Deep learning has revolutionized biomolecular modeling, enabling the prediction of diverse structures with atomic accuracy. However, leveraging the atomic-level precision of the structure prediction model for de novo design remains challenging. Here, we present HalluDesign, a general all-atom framework for protein…
Nghi Huu Duong, Duy Vo, Pruettha Nanakorn
This study proposes an algorithm titled a statistical firefly algorithm (SFA) for truss topology optimization. In the proposed algorithm, historical results of fireflies' motions are used in hypothesis testing to limit the motions of fireflies that are suggested by current information exchanges between fireflies only…
Aiman H. H. Al-Masoodi, Nasir Shafiq, Abtisam Hasan Hamood Al-Masoodi
Recently, there has been advancement in tall building design to achieve lighter structures, which led to an increase in the challenges that are related to wind resistance and cost efficiency. This study is to provide multi-optimization gathering between the aerodynamic optimization with a radial basis function…
Shuzhi Xu, Yifan Guo, Hiroki Kawabe, Kentaro Yaji
Multiscale topology optimization is crucial for designing porous infill structures with high stiffness-toweight ratios and excellent energy absorption. Although gradient-based methods provide a rigorous framework, they are computationally expensive and struggle to capture cross-scale sensitivities in nonlinear…
David Silva-Sánchez, Erik H. Thiede, Roy R. Lederman, Pilar Cossio
Biomolecules are inherently dynamic, and understanding their conformational ensemble distributions is essential for understanding their dynamics and biological roles. Cryo-electron microscopy (cryo-EM), a technique that images individual biomolecules frozen in a thin layer of amorphous ice, has emerged as a leading…
Odin Zhang, Jiaqi Wang, Tuscan Rock Thompson, Ziyi You + 3 more
Biomolecular interactions, including protein–protein interactions, protein–nucleic acid recognition, and protein–small molecule binding, underlie a wide range of biological processes and therapeutic mechanisms. Although recent de novo design methods can generate candidate binders for diverse molecular targets…
Meijun Shang, Xuemei Li, Zhipeng Zhao
Heavy lifting operations performed on basement roof slabs often impose concentrated loads that may cause local stress concentrations, cracking, or even structural failure. To address this issue, this study proposes a heavy-load transfer steel platform supported by basement columns, which effectively isolates the…
Authors not listed
This article presents an overview about the state of the art in the development of structured packings for distillation applications. The focus is on highlighting different approaches including heuristic development cycles, the development of new packing structures, 3D-printing as tool for manufacturing, and…
Hung N. Do, Apoorv Shanker, Ria Q. Kidner, Makaela M. Montoya + 2 more
Signal peptides (SPs) are short amino acid sequences found at the N-terminus of nascent polypeptides, which serve critical roles in trafficking, folding, and post-translational processing of mature proteins. Many sequence-based computational methods have been developed to predict and design optimal SPs for protein…
Piyush Agrawal, Manish Agrawal
The properties of lattice-based structures can be enhanced by varying their geometric parameters in a graded manner, and the gradation can be tailored to extremize a particular objective. In this manuscript, we propose a non-gradient-based optimization framework to find the tailor-made graded profiles for lattice-based…
Fardad Homafar, Jasmin Jelovica
Structural optimization problems often involve a large number of decision variables and highly non-convex feasible regions, making convergence to the true Pareto front extremely challenging. Even when convergence is achievable, it typically requires thousands of function evaluations, resulting in significant…
M. Moustapha, B. Sudret
Reliability-based design optimization (RBDO) is traditionally formulated as a nested optimization and reliability problem. Although surrogate models are generally employed to improve efficiency, the approach remains computationally prohibitive in high-dimensional settings. This paper proposes a novel RBDO framework…
Junqi Wu, Liyan Dong, Nuo Jia, Longyi Li + 1 more
Direct Preference Optimization (DPO) has emerged as a powerful paradigm for aligning generative models, yet its temporal optimization dynamics in the discrete diffusion space of proteins remain poorly understood. Existing approaches often assume that maintaining structural integrity while optimizing physicochemical…
Damian Sokołowski, Tomasz Wudkiewicz, Yuri Ribakov
Highlights 1. Parametric optimization reduced tied-arch footbridge arch-girder weight by 10.7%. 2. Arch rise and hanger number were the key drivers of the minimum-weight design. 3. A Dynamo-Python workflow automated FEM generation and Eurocode-based verification. 4. The optimum solution used a 23.4 m arch rise, 31…
Authors not listed
Thorough treatment of conformation in computational chemistry is required to capture the subtle energy differences that lead to experimental observations. Accurate quantum chemistry calculations are very expensive and evaluation of the entire ensemble found during a conformational search is often unachievable. This is…
Authors not listed
Designing efficient photoreactors remains challenging due to the complex interplay of light transport phenomena, shaped by reflection, scattering and absorption processes. Here, we introduce a workflow that integrates ray-tracing digital twins with multi-objective Bayesian optimization to autonomously design…
Authors not listed
Systematic automated exploration of phase transition pathways enables the elucidation and visualization of potential energy landscapes in crystals. This allows evaluation of not only thermodynamic stability, but also kinetic stability and thermal behavior of metastable structures. Developing computational tools for…
Authors not listed
Incorporating prior domain knowledge into Bayesian optimization (BO) remains difficult for statistical methods, which also typically suffer from limited interpretability. Large language models (LLMs) offer complementary strengths in reasoning and knowledge integration, but it remains unclear when and how they improve…
Authors not listed
Continuous manufacturing processes offer significant advantages over batch processes, including easier scalability, reduced costs, lower raw material and solvent consumption, and improved energy efficiency. A robust techno-economic assessment is therefore essential to evaluate and facilitate the adoption of such…
Authors not listed
Mechanical properties of molecular crystals are fundamentally important to their in- dustrial utility as pharmaceuticals or agrochemicals, energetic materials and more. Yet, complete measurements of elastic tensors are relatively rare and even their theoretical prediction via conventional energy models is not…