Computational Fluid Dynamics (CFD) models are being rapidly integrated into applications across all sciences and engineering. CFD harnesses the power of computers to solve the equations of fluid dynamics, which otherwise cannot be solved analytically...
Background: This study evaluates heuristic and optimization-based methods for minimum-cost distribution flow allocation using discrete-event simulation. Methods: Four distribution networks in Ecuador were modeled in FlexSim 2027, comprising a hypothe...
Reliable debris-flow modelling requires the coupled treatment of rapid free-surface propagation, variable mixture composition, wet–dry fronts, basal resistance, bed exchange, and grain size segregation. This work presents PyDebrisFlow2D, a dept...
The Poisson equation frequently emerges in many fields of science and engineering. As exact solutions are rarely possible, numerical approaches are of great interest. Despite this, a succinct discussion of a systematic approach to constructing a flex...
CFD Julia is a programming module developed for senior undergraduate or graduate-level coursework which teaches the foundations of computational fluid dynamics (CFD). The module comprises several programs written in general-purpose programming langua...
Portfolio optimization is fundamental to modern finance, enabling investors to construct allocations that balance risk and return while satisfying practical constraints. When transaction costs and cardinality limits are incorporated, the problem beco...
A Python non-uniform fast Fourier transform (PyNUFFT) package has been developed to accelerate multidimensional non-Cartesian image reconstruction on heterogeneous platforms. Since scientific computing with Python encompasses a mature and integrated...
In this paper, we investigate the feasibility of using DNS data and machine learning algorithms to assist RANS turbulence model development. High-fidelity DNS data are generated with the incompressible Navier–Stokes solver implemented in the spectral...
At the core of every system for the efficient control of the network steady-state operation is the AC-power-flow problem solver. For local distribution networks to continue to operate effectively, it is necessary to use the most powerful and numerica...
Geometric problem solving (GPS) has always been a long-standing challenge in the fields of automated reasoning. Its problem representation and solution process embody rich symmetry. This paper is the second in a series of our works. Based on the Geom...
A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using s...
With the global rise in consumer electronics, electric vehicles, and renewable energy, the demand for lithium-ion batteries (LIBs) is expected to grow. LIBs present a significant challenge for state estimations due to their complex non-linear electro...
The increasing demand for rapid and sustainable parcel delivery has motivated the exploration of innovative logistics systems that integrate drones with traditional ground vehicles. Among these, the single-truck, multiple-drone last-mile delivery con...
The Wind Synthesis System using Doppler Measurements (WISSDOM) retrieves three-dimensional winds by minimizing a variational objective that combines Doppler-radar observations and physical constraints. Using a common Python implementation with PyTorc...
This work presents the design and implementation of an automated, digital, and modular system to address a real-world industrial challenge: the automation and optimization of production schedules for Computer Numerical Control (CNC) machines in a fac...
Machine learning based on neural networks facilitates data-driven techniques for handling large amounts of data, either obtained through experiments or simulations at multiple spatio-temporal scales, thereby finding the hidden patterns underlying the...
Referencing ion exchange applied in the extraction of ion-adsorption minerals, a mathematical model based on thermodynamic equilibrium has been researched and established to reveal and represent the chemical reaction between minerals and the leaching...
A previously published, experimentally validated fed-batch reactor model for production of monoclonal antibodies (mAbs) via a fermentation process (which includes substrate consumption by cells, resulting in biomass growth and product formation) is e...
28 September 2026
Open-RPS v1.0 (radial power solver) is an open-source software platform for three-phase power flow analysis in balanced and unbalanced radial distribution systems. The platform implements the backward/forward sweep (BFS) method in Python through an o...
A time-lock puzzle encapsulates a secret message such that the receiver needs to perform a sequential computation, which takes a specified amount of time, to recover the message. Time-lock puzzles can be used in various scenarios, such as sealed-bid...
Finding the optimal speed profile of an autonomous electric vehicle (AEV) for a given route (eco-driving) can lead to a reduction in energy consumption. This energy reduction is even more noticeable when the regenerative braking (RB) capability of AE...
Topology optimization has evidenced its capacity to provide new optimal designs in many different disciplines. However, most novel methods are difficult to apply in commercial software, limiting their use in the academic field and hindering their app...
In the packaging industry, corrugated boards are widely used due to many factors like biodegradability, a high strength-to-weight ratio, and also ease of manufacturing. In this study, the finite element analysis of corrugated cardboards under the fla...
DynPy is an open-source library implemented in Python (version 3.10.12) programming language which aims to provide a versatile set of functionalities for mechanical and electrical engineers. It enables the user to model, solve, simulate, and report a...
Linear latent variable models such as principal component analysis (PCA), independent component analysis (ICA), canonical correlation analysis (CCA), and factor analysis (FA) identify latent directions (or loadings) either ordered or unordered. These...
Background: Logistics operations are integral to manufacturing systems, particularly in the transportation processes that occur not only between facilities and stakeholders but also between warehouses and workstations within a facility. The design of...
While multi-model assembly lines are used by advanced lean companies because of their flexibility (different models of a product are produced in small lots and reach the customers in a short lead time), most of the extant literature on how to staff a...
The study of heat transfer deals with the determination of the rate of heat energy transfer from one system to another driven by a temperature gradient. It can be observed in many natural phenomena and is often the fundamental principle behind severa...
Piping systems (e.g., storm sewers) that transition between free-surface flow and surcharged flow are challenging to model in one-dimensional (1D) networks as the continuity equation changes from hyperbolic to elliptic as the water surface reaches th...
The Korteweg–de Vries (KdV) equation is a foundational model in geophysical fluid dynamics (GFD), governing the propagation of long internal and surface gravity waves in stratified and shallow ocean environments where the interplay between nonl...
This paper presents automatic software for E-liked shaped contactless inductive power transfer (CIPT) device study and design that provides attended-free, multiple-case auto-generating and auto-deploying analysis in one go. It provides visualized and...
Stress–strain data with a given constitutive model of material can be calculated directly at a single material point. In this work, we propose a framework to perform single-point calculations under large deformations with stress and mixed contr...
The accurate prediction of crack initiation and propagation is essential for assessing the structural integrity of mechanically joined components and other complex assemblies. To overcome the limitations of existing finite element tools, a modular Py...
When a pulsed, few-cycle electromagnetic wave is focused by optics with f-number smaller than two, the frequency components it contains are focused to different regions of space, building up a complex electromagnetic field structure. Accurate numeric...
Factors such as persistent demand growth, expansion project delays, and the rising adoption of renewable energy sources highlight the importance of operating power systems within safe operational margins. The optimal reactive power dispatch (ORPD) se...
A new methodology, called HY4RES models, includes hybrid energy solutions (HESs) based on the availability of renewable sources, for 24 h of water allocation, using WaterGEMS 10.0 and PVGIS 5.2 as auxiliary calculations. The optimization design was a...
A new methodology for hybrid energy systems (HESs) was developed, namely the HY4RES model, tailored for the water sector, covering hybrid energy objective functions and grid or battery support using optimization algorithms in Solver, MATLAB, and Pyth...
Current trends in the aerospace and UAV sectors emphasize integrating Artificial Intelligence (AI) technologies into the design process. AI technologies necessitate extensive data to capture the non-linearities in fluid phenomena. To address these ne...
The increasing complexity of the UAV aerodynamic design, imposed by novel configurations and requirements, has highlighted the need for efficient tools for high-fidelity simulation, especially for optimization purposes. The current work presents an a...
This study presents a frequency-domain analysis of a finite-element (FEM)-based rotor–nacelle model for wind turbines, validated against the open-source time-domain tool OpenFAST. The analysis was carried out using METHOD, an in-house computati...
The world’s demand for electrical energy is increasing rapidly while the use of fossil fuels is getting limited more and more by energy policies and the need for reducing the impact of climate change. New sources of energy are required to fulfill the...
Despite the increasing interest in organic Rankine cycle (ORC) systems and the large number of cycle models proposed in the literature, charge-based ORC models are still almost absent. In this paper, a detailed overall ORC simulation model is present...
Nanofluids, which are suspensions of nanoparticles within base fluids, are employed in industries such as electronics, automotives, nuclear power, and defense to enhance thermal management, mass transfer, and microchip cooling. This study investigate...
This paper investigates the optimization of maintenance strategies to improve the reliability of equipment at the Kapshagay Hydropower Plant (HPP), located in Kazakhstan. Operational data for the period 2020–2025 were analyzed to evaluate the e...
The rise in thermal runaway events within electric vehicle (EV) battery systems requires anticipatory models to predict critical safety failures during operation. This investigation develops a multi-physics digital twin framework that links electroch...
Background/Objectives: Advancements in personalized medicine have revolutionized drug delivery, enabling tailored treatments based on genetic and molecular profiles. Non-viral vectors, such as polyurethane (PU)-based systems, offer promising alternat...
The integration of quantitative mathematical methods and artificial intelligence into agricultural monitoring systems represents a critical pathway toward data-driven decision-making in the contemporary precision agriculture economy. This study appli...
A rapid quasi-one-dimensional (quasi-1D) reacting-flow analysis code was developed for the preliminary assessment of rocket-based combined cycle engines over a broad flight envelope. The internal flow was modeled as steady and quasi-1D in a variable-...
Mathematical optimization, in both continuous and discrete forms, is well established and widely applied. This work addresses a gap in the literature by focusing on large-number optimization, where integers or fractions with hundreds of digits occur...
A substantial body of phenomenological and theoretical work over the last few years strengthens the possibility that the vacuum energy density (VED) of the universe is dynamical, and in particular that it adopts the ‘running vacuum model’...
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