计算工程、金融与科学

The automotive industry runs on a dense, standardised chain of supplier-quality and certification evidence: production part approval packages, initial sample reports, material certificates, inspection sign-offs, and the type approval…

This work proposes a novel continuum damage framework for fatigue based on the endurance-surface concept and uses the energy-release rate as the driving force. Damage evolution is governed by the distance of the thermodynamic driving force…

We introduce an adjoint-based reduced-order model framework for fast and accurate estimation of quantities of interest for many-query linear problems. The method builds a reduced-order model with respect to the adjoint problem, thus…

We develop a repair-oriented inspection and maintenance decision framework for water distribution networks. This work is motivated by utilities operating in data-sparse environments, such as in remote locations like the U.S. Virgin Islands,…

Glioblastoma progression is strongly influenced by evolving mechanical interactions between the tumor and surrounding brain tissue. However, the extent to which finite-deformation mechanics and constitutive assumptions improve…

A linear probe that recovers a conserved quantity from a learned dynamics model's activations is routinely read as evidence that the model uses that quantity. We show this inference is unsound. Across mechanical, circuit, and…

Bitcoin (BTC) wealth distribution is often studied with macro indicators like wallet balances, prices, network activity, fees, and hashrate. This letter proposes a "Crypto-Microeconomic Observability Framework" to examine micro-level…

The uncertainty associated with breakup events that occur during atmospheric re-entry is severe. Limited attempts to gain a better knowledge of this environment have included the use of breakup recorder-type sensor capsules that are…

Bitcoin research increasingly relies on on-chain indicators to study network activity, monetary issuance, transaction demand, miner incentives, coin-age behavior, and long-run monetary dynamics. However, many commonly used Bitcoin metrics…

Information Systems research increasingly relies on machine learning (ML) to predict outcomes in complex sociotechnical systems, yet predictive models are not designed to identify causal effects. This limitation is particularly critical in…

Topology optimization (TO) has become a mature computational design method, but using it still requires substantial manual effort in geometry preparation, mesh generation, boundary-condition assignment, solver setup, and postprocessing.…

Computational biomechanics increasingly requires models that combine mechanics, transport, chemistry, and biological regulation across different spatial and temporal scales. The FEBio simulation software provides extensive open-source…

Abdominal aortic aneurysm (AAA) rupture risk assessment increasingly relies on patient-specific biomechanical computations, which require accurate three-dimensional aneurysm geometry from computed tomography angiography (CTA). Manual and…

Predicting complex spatiotemporal dynamics in physical processes often demands computationally expensive numerical methods or data-driven neural networks that suffer from high training costs, error accumulation, and limited generalizability…

We propose an explainable quantum neural network for multi-material topology optimization, XQNN, that determines both load-carrying structural layout and material type assignment for given boundary/loading conditions. Intermediate solution…

This paper presents a comprehensive geometric and computational framework for the generation of the complete Pareto frontier. Several existing methods are structurally unable to capture the complete admissible Pareto region. These include…

Traditional metrics for Medical Report Generation (MRG) predominantly rely on surface-level n-gram overlap, which fails to capture clinical factual accuracy and often overlooks catastrophic diagnostic errors. We address this fundamental…

Soft actuators, characterized by their compliance and flexibility, have tremendous potential for diverse applications, ranging from medical devices to submarine operations. However, significant challenges remain in the design of these…

Elastic guided waves are widely used in Structural Health Monitoring (SHM). In many-query settings, the computational cost of high-fidelity simulations motivates the use of projection-based reduced order modeling (ROM). However, the…

We present a scalable AI-driven framework that advances autonomous scientific discovery by combining agentic workflow automation, high-performance computing, and scientific surrogate models. Using microkinetics discovery as a testbed, the…