Hasil untuk "Environmental engineering"

J. Choi, Sang-Soo Han, Hak-Sung Kim

M. Elimelech

Secondary Pollutants

The Environmental Pollution book series includes current, comprehensive texts on critical national and global environmental issues useful to scientists in academia, industry and government from diverse disciplines. These include water, air, and soil pollution, organic and inorganic pollution, risk assessment, human and environmental health, environmental biotechnology, global ecology, mathematics and computing as related to environmental pollution, environmental modelling, environmental chemistry and physics, biology, toxicology, conservation and biodiversity, agricultural sciences, pesticides, environmental engineering, bioremediation/biorestoration, and environmental economics. Environmental problems and solutions are complex and interrelated. Complex problems often require complex solutions. The linkage of many disciplines can result in new approaches to old and new environmental problems as well as pollution prevention. This knowledge will assist in understanding, maintaining and improving the biosphere in which we live. Proposals for this book series can be sent the Series Editor: Jack Trevors at jtrevors@uoguelph.ca or the Publishing Editor Sherestha Saini at Sherestha.Saini@springer.com

M. Patel

Wind and Solar Power Systems provides a comprehensive treatment of this rapidly growing segment of the power industry. It presents the fundamentals of wind and solar power generation, energy conversion and storage, and the operational aspects of power electronics and the quality of power. It covers in detail design, operation, and control methods and discusses the present status of and the on-going research in renewable power around the world. This book is among the most modern, complete texts available on renewable energy. Electrical, environmental and mechanical engineering professionals and policy-makers will find in it the background and the details they need.

S. Lee, H. Kim, Tong Un Chae et al.

Yancheng Li, Jianchun Li, Weihua Li et al.

A. Zeraatkar, H. Ahmadzadeh, A. Talebi et al.

R. Taylor

Foreword - A N Schofield Geotechnical centrifuges: past, present and future - Dr W H Craig Centrifuge modelling: practical considerations - R N Taylor Retaining walls and soil-structure interaction - W Powrie Buried structures and underground excavations - R N Taylor Foundations - O Kusakabe Dynamics - R S Steedman and X Zeng Environmental geomechanics and transport processes- P J Culligan-Hensley and C Savvidou Cold regions' engineering - C C Smith Conclusions. Appendix. References.

Y. Gan, A. Jayatissa, Zhenlu Yu et al.

Department of Mechanical Engineering, California State Polytechnic University Pomona, 3801 W. Temple Avenue, Pomona, CA 91768, USA Department of Mechanical, Industrial and Manufacturing Engineering, University of Toledo, 2801 W. Bancroft Street, Toledo, OH 43606, USA Department of Electrical and Computer Engineering, California State Polytechnic University Pomona, 3801 W. Temple Avenue, Pomona, CA 91768, USA Department of Earth and Environmental Engineering, Columbia University, 500 W. 120th Street, New York, NY 10027, USA Department of Chemical and Materials Engineering, California State Polytechnic University Pomona, 3801 W. Temple Avenue, Pomona, CA 91768, USA

Guangdong Tian, Wei Lu, Xuesong Zhang et al.

Jiahong Xiang, Wenxiao He, Xihua Wang et al.

The Rust programming language presents a steep learning curve and significant coding challenges, making the automation of issue resolution essential for its broader adoption. Recently, LLM-powered code agents have shown remarkable success in resolving complex software engineering tasks, yet their application to Rust has been limited by the absence of a large-scale, repository-level benchmark. To bridge this gap, we introduce Rust-SWE-bench, a benchmark comprising 500 real-world, repository-level software engineering tasks from 34 diverse and popular Rust repositories. We then perform a comprehensive study on Rust-SWE-bench with four representative agents and four state-of-the-art LLMs to establish a foundational understanding of their capabilities and limitations in the Rust ecosystem. Our extensive study reveals that while ReAct-style agents are promising, i.e., resolving up to 21.2% of issues, they are limited by two primary challenges: comprehending repository-wide code structure and complying with Rust's strict type and trait semantics. We also find that issue reproduction is rather critical for task resolution. Inspired by these findings, we propose RUSTFORGER, a novel agentic approach that integrates an automated test environment setup with a Rust metaprogramming-driven dynamic tracing strategy to facilitate reliable issue reproduction and dynamic analysis. The evaluation shows that RUSTFORGER using Claude-Sonnet-3.7 significantly outperforms all baselines, resolving 28.6% of tasks on Rust-SWE-bench, i.e., a 34.9% improvement over the strongest baseline, and, in aggregate, uniquely solves 46 tasks that no other agent could solve across all adopted advanced LLMs.

R. Lent, Steven D. Brown, Hung-Bin Sheu et al.

Hao Li, Yongkang Qi, Minru Su et al.

Electrodes with high activation efficiency and stability are critical for the electrochemical activation of persulfate. In this study, the effective degradation of acid orange 74 (AO 74) was achieved using the electrochemically activated peroxydisulfate (PDS) with a Ag nanoparticle–modified carbon paper (AgNPs@CP) electrode, demonstrating a 2.5-fold enhancement in the AO 74 degradation rate compared with the CP electrode. The impact of reaction conditions, including AgNPs dosage, PDS content, current density, initial solution pH, and agitation rate, as well as water matrices, such as Cl−, CO32−, and SO42−, on AO 74 degradation was systematically investigated to establish optimal parameters. Radical quenching experiments and electron paramagnetic resonance analysis identified sulfate radical and hydroxyl radical as the dominant reactive species. Gas chromatography–mass spectrometry analysis revealed that AO 74 was primarily transformed into aliphatic organic compounds during electrochemical degradation. Remarkably, the 3-h AO 74 degradation efficiency remained stable over five consecutive cycles through alternating use of the AgNPs@CP anode and CP cathode, facilitated by Ag0/Ag+/Ag2+ redox cycling that enabled Ag recovery and minimized Ag leaching. The electrochemically activated PDS with the AgNPs@CP electrode shows promise as a pretreatment technology for dyeing wastewater with low biodegradability.

Divya Nimma, Okram Ricky Devi, Bibek Laishram et al.

Global warming is a phenomenon whereby the planet's exposure to the sun's radiation worsens from the high emission of gasses believed to trap heat within the atmosphere. Carbon dioxide (CO2) is the leading greenhouse gas majorly responsible for global warming and other related issues and is a danger to global society. This one has a particular role in portraying the key importance of the shifting climate that invariably influences water supply and agricultural production. Global warming presents complex challenges to aquatic organisms and stocks and other natural aquatic life resources. This study examines how freshwater and marine species are affected by climate change in aquatic habitats. Aquatic species' metabolism, growth, reproduction, and dispersal are all impacted by rising temperatures and altered water chemistry brought on by increased greenhouse gas emissions, especially CO2. The goal is to pinpoint the ecosystems and vulnerable species that are most impacted by these changes and suggest flexible management techniques. The suggested remedies center on creating sustainable conservation strategies that lessen the effects of climate change on aquatic biodiversity and increase these ecosystems' resilience. The socio-economic interdependencies between water and climate change impact agricultural and water resources, and the pressures exerted on water bodies and water supply landscapes. Another area is related to alterations in the physical and chemical properties of the water, such as the temperature, which is a well-known effect of climate change: 'This causes abnormalities in the metabolism and physiology of aquatic species.' These alterations flow through the chain and regime of growth, reproduction, feeding habits and distribution, migration, and mass of fish and other creatures in the water system. However, the long-term effect of climate variation and climate change on freshwater ecosystems requires much scientific investigation to address challenges in aquatic ecosystem conservation and sustainability. This being the case, adaptive management solutions that address the interrelated impacts of climate change have to be applied and implemented to reduce vulnerability in aquatic ecosystems worldwide.

Muhammad Tayyab Khan, Zane Yong, Lequn Chen et al.

Engineering drawings are fundamental to manufacturing communication, serving as the primary medium for conveying design intent, tolerances, and production details. However, interpreting complex multi-view drawings with dense annotations remains challenging using manual methods, generic optical character recognition (OCR) systems, or traditional deep learning approaches, due to varied layouts, orientations, and mixed symbolic-textual content. To address these challenges, this paper proposes a three-stage hybrid framework for the automated interpretation of 2D multi-view engineering drawings using modern detection and vision language models (VLMs). In the first stage, YOLOv11-det performs layout segmentation to localize key regions such as views, title blocks, and notes. The second stage uses YOLOv11-obb for orientation-aware, fine-grained detection of annotations, including measures, GD&T symbols, and surface roughness indicators. The third stage employs two Donut-based, OCR-free VLMs for semantic content parsing: the Alphabetical VLM extracts textual and categorical information from title blocks and notes, while the Numerical VLM interprets quantitative data such as measures, GD&T frames, and surface roughness. Two specialized datasets were developed to ensure robustness and generalization: 1,000 drawings for layout detection and 1,406 for annotation-level training. The Alphabetical VLM achieved an overall F1 score of 0.672, while the Numerical VLM reached 0.963, demonstrating strong performance in textual and quantitative interpretation, respectively. The unified JSON output enables seamless integration with CAD and manufacturing databases, providing a scalable solution for intelligent engineering drawing analysis.

Johan Cederbladh, Loek Cleophas, Eduard Kamburjan et al.

With the current trend in Model-Based Systems Engineering towards Digital Engineering and early Validation & Verification, experiments are increasingly used to estimate system parameters and explore design decisions. Managing such experimental configuration metadata and results is of utmost importance in accelerating overall design effort. In particular, we observe it is important to 'intelligent-ly' reuse experiment-related data to save time and effort by not performing potentially superfluous, time-consuming, and resource-intensive experiments. In this work, we present a framework for managing experiments on digital and/or physical assets with a focus on case-based reasoning with domain knowledge to reuse experimental data efficiently by deciding whether an already-performed experiment (or associated answer) can be reused to answer a new (potentially different) question from the engineer/user without having to set up and perform a new experiment. We provide the general architecture for such an experiment manager and validate our approach using an industrial vehicular energy system-design case study.

Daniel N. Wilke

This paper introduces Design for Sensing and Digitalisation (DSD), a new engineering design paradigm that integrates sensor technology for digitisation and digitalisation from the earliest stages of the design process. Unlike traditional methodologies that treat sensing as an afterthought, DSD emphasises sensor integration, signal path optimisation, and real-time data utilisation as core design principles. The paper outlines DSD's key principles, discusses its role in enabling digital twin technology, and argues for its importance in modern engineering education. By adopting DSD, engineers can create more intelligent and adaptable systems that leverage real-time data for continuous design iteration, operational optimisation and data-driven predictive maintenance.

Muhammad Tayyab Khan, Zane Yong, Lequn Chen et al.

Accurate extraction of key information from 2D engineering drawings is crucial for high-precision manufacturing. Manual extraction is slow and labor-intensive, while traditional Optical Character Recognition (OCR) techniques often struggle with complex layouts and overlapping symbols, resulting in unstructured outputs. To address these challenges, this paper proposes a novel hybrid deep learning framework for structured information extraction by integrating an Oriented Bounding Box (OBB) detection model with a transformer-based document parsing model (Donut). An in-house annotated dataset is used to train YOLOv11 for detecting nine key categories: Geometric Dimensioning and Tolerancing (GD&T), General Tolerances, Measures, Materials, Notes, Radii, Surface Roughness, Threads, and Title Blocks. Detected OBBs are cropped into images and labeled to fine-tune Donut for structured JSON output. Fine-tuning strategies include a single model trained across all categories and category-specific models. Results show that the single model consistently outperforms category-specific ones across all evaluation metrics, achieving higher precision (94.77% for GD&T), recall (100% for most categories), and F1 score (97.3%), while reducing hallucinations (5.23%). The proposed framework improves accuracy, reduces manual effort, and supports scalable deployment in precision-driven industries.

Thiago Barradas, Aline Paes, Vânia de Oliveira Neves

The effective execution of tests for REST APIs remains a considerable challenge for development teams, driven by the inherent complexity of distributed systems, the multitude of possible scenarios, and the limited time available for test design. Exhaustive testing of all input combinations is impractical, often resulting in undetected failures, high manual effort, and limited test coverage. To address these issues, we introduce RestTSLLM, an approach that uses Test Specification Language (TSL) in conjunction with Large Language Models (LLMs) to automate the generation of test cases for REST APIs. The approach targets two core challenges: the creation of test scenarios and the definition of appropriate input data. The proposed solution integrates prompt engineering techniques with an automated pipeline to evaluate various LLMs on their ability to generate tests from OpenAPI specifications. The evaluation focused on metrics such as success rate, test coverage, and mutation score, enabling a systematic comparison of model performance. The results indicate that the best-performing LLMs - Claude 3.5 Sonnet (Anthropic), Deepseek R1 (Deepseek), Qwen 2.5 32b (Alibaba), and Sabia 3 (Maritaca) - consistently produced robust and contextually coherent REST API tests. Among them, Claude 3.5 Sonnet outperformed all other models across every metric, emerging in this study as the most suitable model for this task. These findings highlight the potential of LLMs to automate the generation of tests based on API specifications.

Pierre-Emmanuel Goffi, Raphaël Tremblay, Bentley Oakes

Successfully engineering interactive industrial DTs is a complex task, especially when implementing services beyond passive monitoring. We present here an experience report on engineering a safety-critical digital twin (DT) for beer fermentation monitoring, which provides continual sampling and reduces manual sampling time by 91%. We document our systematic methodology and practical solutions for implementing bidirectional DTs in industrial environments. This includes our three-phase engineering approach that transforms a passive monitoring system into an interactive Type 2 DT with real-time control capabilities for pressurized systems operating at seven bar. We contribute details of multi-layered safety protocols, hardware-software integration strategies across Arduino controllers and Unity visualization, and real-time synchronization solutions. We document specific engineering challenges and solutions spanning interdisciplinary integration, demonstrating how our use of the constellation reporting framework facilitates cross-domain collaboration. Key findings include the critical importance of safety-first design, simulation-driven development, and progressive implementation strategies. Our work thus provides actionable guidance for practitioners developing DTs requiring bidirectional control in safety-critical applications.