Hasil untuk "Low temperature engineering. Cryogenic engineering. Refrigeration"

Mairieli Wessel, Daniel Feitosa, Sangeeth Kochanthara

Rising publication pressure and the routine use of generative AI tools are reshaping how software engineering research is produced, assessed, and taught. While these developments promise efficiency, they also raise concerns about skill degradation, responsibility, and trust in scholarly outputs. This vision paper employs Design Fiction as a methodological lens to examine how such concerns might materialise if current practices persist. Drawing on themes reported in a recent community survey, we construct a speculative artifact situated in a near future research setting. The fiction is used as an analytical device rather than a forecast, enabling reflection on how automated assistance might impede domain knowledge competence, verification, and mentoring practices. By presenting an intentionally unsettling scenario, the paper invites discussion on how the software engineering research community in the future will define proficiency, allocate responsibility, and support learning.

Golnoush Abaei, Mojtaba Shahin, Maria Spichkova

The inclusion of internship courses in Software Engineering (SE) programs is essential for closing knowledge gaps and improving graduates' readiness for the software industry. Our study focuses on year-long internships at RMIT University (Melbourne, Australia), which offers in-depth industry engagement. We analysed how the course evolved over the last 10 years to incorporate students' needs and summarised the lessons learned that can be helpful for other educators supporting internship courses. Our qualitative analysis of internship data based on 91 reports during 2023-2024 identified three challenge themes the students faced, and which courses were found by students to be particularly beneficial during their internships. On this basis, we proposed recommendations for educators and companies to help interns overcome challenges and maximise their learning experience.

Massimiliano Di Penta, Kelly Blincoe, Marsha Chechik et al.

As software engineering conferences grow in size, rising costs and outdated formats are creating barriers to participation for many researchers. These barriers threaten the inclusivity and global diversity that have contributed to the success of the SE community. Based on survey data, we identify concrete actions the ACM Special Interest Group on Software Engineering (SIGSOFT) can take to address these challenges, including improving transparency around conference funding, experimenting with hybrid poster presentations, and expanding outreach to underrepresented regions. By implementing these changes, SIGSOFT can help ensure the software engineering community remains accessible and welcoming.

Ana B. M. Bett, Thais S. Nepomuceno, Edson OliveiraJr et al.

Context: The empirical software engineering (ESE) community has contributed to improving experimentation over the years. However, there is still a lack of rigor in describing controlled experiments, hindering reproducibility and transparency. Registered Reports (RR) have been discussed in the ESE community to address these issues. A RR registers a study's hypotheses, methods, and/or analyses before execution, involving peer review and potential acceptance before data collection. This helps mitigate problematic practices such as p-hacking, publication bias, and inappropriate post hoc analysis. Objective: This paper presents initial results toward establishing an RR template for Software Engineering controlled experiments using the Open Science Framework (OSF). Method: We analyzed templates of selected OSF RR types in light of documentation guidelines for controlled experiments. Results: The observed lack of rigor motivated our investigation of OSF-based RR types. Our analysis showed that, although one of the RR types aligned with many of the documentation suggestions contained in the guidelines, none of them covered the guidelines comprehensively. The study also highlights limitations in OSF RR template customization. Conclusion: Despite progress in ESE, planning and documenting experiments still lack rigor, compromising reproducibility. Adopting OSF-based RRs is proposed. However, no currently available RR type fully satisfies the guidelines. Establishing RR-specific guidelines for SE is deemed essential.

Haohao Hou, Yu Xue, Meng Zhang et al.

Polypropylene homopolymer (PPH) is a highly practical and widely utilized thermoplastic polymer that finds extensive applications in automotive components, piping systems, and constructed materials. Although PPH has merits such as low cost, versatility, and exceptional corrosion resistance, its low toughness limits application in specialized engineering sectors such as high‐pressure piping, aerospace components, and cryogenic environments. In this paper, the toughness of PPH was improved by blending with polypropylene block copolymer (PPB) and β nucleating agent (NP‐328). The room temperature impact strength of PPH containing 30% PPB and 0.2% NP‐328 was increased by 4.4 times, and its low‐temperature elongation at break was improved by 87%, compared to those of the pure PPH sample. Furthermore, this paper investigated the crystallization behaviors of PPH/PPB(70/30) with varying amounts of NP‐328, using crystallization kinetics studies for analysis. The crystallization rate of PPH/PPB (70/30) systems gradually adding the amounts of NP‐328 improved significantly. At 140°C, the half‐crystallization time of the PPH/PPB (70/30) containing 0.2% NP‐328 decreased by 14.5 min compared with that of PPH/PPB (70/30) without NP‐328. The high‐toughness PPH material developed in this work exhibits significant potential for application across a variety of industries, including automotive manufacturing, home appliance production, and packaging sector, among others.

Zirui Li, Stephan Husung, Haoze Wang

Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across independently developed system models. SysML v2 introduces enhanced structural modularity and formal semantics, offering a stronger foundation for interoperable modeling. Meanwhile, GPT-based Large Language Models (LLMs) provide new capabilities for assisting model understanding and integration. This paper proposes a structured, prompt-driven approach for LLM-assisted semantic alignment of SysML v2 models. The core contribution lies in the iterative development of an alignment approach and interaction prompts, incorporating model extraction, semantic matching, and verification. The approach leverages SysML v2 constructs such as alias, import, and metadata extensions to support traceable, soft alignment integration. It is demonstrated with a GPT-based LLM through an example of a measurement system. Benefits and limitations are discussed.

Jake Zappin, Trevor Stalnaker, Oscar Chaparro et al.

This position paper examines the substantial divide between academia and industry within quantum software engineering. For example, while academic research related to debugging and testing predominantly focuses on a limited subset of primarily quantum-specific issues, industry practitioners face a broader range of practical concerns, including software integration, compatibility, and real-world implementation hurdles. This disconnect mainly arises due to academia's limited access to industry practices and the often confidential, competitive nature of quantum development in commercial settings. As a result, academic advancements often fail to translate into actionable tools and methodologies that meet industry needs. By analyzing discussions within quantum developer forums, we identify key gaps in focus and resource availability that hinder progress on both sides. We propose collaborative efforts aimed at developing practical tools, methodologies, and best practices to bridge this divide, enabling academia to address the application-driven needs of industry and fostering a more aligned, sustainable ecosystem for quantum software development.

Martin Obaidi, Marc Herrmann, Jil Klünder et al.

Software development relies heavily on text-based communication, making sentiment analysis a valuable tool for understanding team dynamics and supporting trustworthy AI-driven analytics in requirements engineering. However, existing sentiment analysis tools often perform inconsistently across datasets from different platforms, due to variations in communication style and content. In this study, we analyze linguistic and statistical features of 10 developer communication datasets from five platforms and evaluate the performance of 14 sentiment analysis tools. Based on these results, we propose a mapping approach and questionnaire that recommends suitable sentiment analysis tools for new datasets, using their characteristic features as input. Our results show that dataset characteristics can be leveraged to improve tool selection, as platforms differ substantially in both linguistic and statistical properties. While transformer-based models such as SetFit and RoBERTa consistently achieve strong results, tool effectiveness remains context-dependent. Our approach supports researchers and practitioners in selecting trustworthy tools for sentiment analysis in software engineering, while highlighting the need for ongoing evaluation as communication contexts evolve.

Dehai Zhao, Zhenchang Xing, Qinghua Lu et al.

UI automation is a useful technique for UI testing, bug reproduction, and robotic process automation. Recording user actions with an application assists rapid development of UI automation scripts, but existing recording techniques are intrusive, rely on OS or GUI framework accessibility support, or assume specific app implementations. Reverse engineering user actions from screencasts is non-intrusive, but a key reverse-engineering step is currently missing - recognizing human-understandable structured user actions ([command] [widget] [location]) from action screencasts. To fill the gap, we propose a deep learning-based computer vision model that can recognize 11 commands and 11 widgets, and generate location phrases from action screencasts, through joint learning and multi-task learning. We label a large dataset with 7260 video-action pairs, which record user interactions with Word, Zoom, Firefox, Photoshop, and Windows 10 Settings. Through extensive experiments, we confirm the effectiveness and generality of our model, and demonstrate the usefulness of a screencast-to-action-script tool built upon our model for bug reproduction.

Roham Koohestani, Philippe de Bekker, Begüm Koç et al.

Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for tasks such as code generation and bug repair. However, this proliferation has led to major challenges: (1) fragmented knowledge across tasks, (2) difficulty in selecting contextually relevant benchmarks, (3) lack of standardization in benchmark creation, and (4) flaws that limit utility. Addressing these requires a dual approach: systematically mapping existing benchmarks for informed selection and defining unified guidelines for robust, adaptable benchmark development. We conduct a review of 247 studies, identifying 273 AI4SE benchmarks since 2014. We categorize them, analyze limitations, and expose gaps in current practices. Building on these insights, we introduce BenchScout, an extensible semantic search tool for locating suitable benchmarks. BenchScout employs automated clustering with contextual embeddings of benchmark-related studies, followed by dimensionality reduction. In a user study with 22 participants, BenchScout achieved usability, effectiveness, and intuitiveness scores of 4.5, 4.0, and 4.1 out of 5. To improve benchmarking standards, we propose BenchFrame, a unified framework for enhancing benchmark quality. Applying BenchFrame to HumanEval yielded HumanEvalNext, featuring corrected errors, improved language conversion, higher test coverage, and greater difficulty. Evaluating 10 state-of-the-art code models on HumanEval, HumanEvalPlus, and HumanEvalNext revealed average pass-at-1 drops of 31.22% and 19.94%, respectively, underscoring the need for continuous benchmark refinement. We further examine BenchFrame's scalability through an agentic pipeline and confirm its generalizability on the MBPP dataset. All review data, user study materials, and enhanced benchmarks are publicly released.

Jia-Bao Yan

Construction of infrastructures in cold regions and the Arctic has grown rapidly since the 2000s, including railways, platforms, bridges, roads, and pipelines. However, the harsh low temperatures significantly influence the mechanical behaviors of construction materials, and bring safety and durability challenges to these engineering structures. This study made a state‐of‐the‐art review on materials and structures exposed to low temperatures. This review started from constructional‐material mechanical properties, including concrete, steel reinforcement, mild/high‐strength steel plate, and steel strand at low temperatures. It reflected that low temperatures improved the strength of construction materials. However, the freeze–thaw cycles (FTCs) had a detrimental effect on the modulus and strength of concrete. Furthermore, it was revealed that low temperatures increased the interfacial bonding strength between the steel reinforcements (or shear connectors) and concrete. Moreover, low temperatures improved the bending, shear, and compression resistances of reinforced concrete (RC) or prestressed concrete structures, but reduced the ductility of RC columns under lateral cyclic loads. Finally, reviews also found that low temperatures improved the compression resistance of concrete‐filled steel tubes using mild, high‐strength, and stainless steels, whereas FTCs and erosion reduced their compression capacity. In addition, low temperatures increased the bending resistance of steel–concrete composite structures, but the FTCs reduced it. The low temperatures bring challenges to the safety and resilience of engineering constructions, which requires careful further studies. Continuous further studies may focus on the durability of materials and the resilience of structures under diverse hazards, including earthquakes, impacts, and even blasts.

Dejene Tadesse Banjaw, Habtamu Gudisa Megersa

Garlic is a versatile vegetable commonly grown in subtropical and highland agroecosystems, which is utilized for its culinary, medicinal, and spice properties. The use of garlic as a medicinal aid can be traced back to ancient times. The health benefits of garlic production are attributed to its antiviral, antibacterial, and antifungal properties. The use of garlic is prevalent in both traditional and modern healthcare systems, where it is used to treat a wide range of conditions. Numerous studies have reported the therapeutic properties of garlic, and its effectiveness has been demonstrated in clinical trials. The growing global interest in health and wellness, the widespread use of garlic as a spice, and its potential economic, social, and health benefits have contributed to a surge in its demand worldwide. This review aims to provide a comprehensive overview of the scientific literature on the morphological descriptions of garlic and its nutritional and health significance.

Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais et al.

Graphical User Interfaces (GUIs) are central to app development projects. App developers may use the GUIs of other apps as a means of requirements refinement and rapid prototyping or as a source of inspiration for designing and improving their own apps. Recent research has thus suggested retrieving relevant GUI designs that match a certain text query from screenshot datasets acquired through crowdsourced or automated exploration of GUIs. However, such text-to-GUI retrieval approaches only leverage the textual information of the GUI elements, neglecting visual information such as icons or background images. In addition, retrieved screenshots are not steered by app developers and lack app features that require particular input data. To overcome these limitations, this paper proposes GUing, a GUI search engine based on a vision-language model called GUIClip, which we trained specifically for the problem of designing app GUIs. For this, we first collected from Google Play app introduction images which display the most representative screenshots and are often captioned (i.e.~labelled) by app vendors. Then, we developed an automated pipeline to classify, crop, and extract the captions from these images. This resulted in a large dataset which we share with this paper: including 303k app screenshots, out of which 135k have captions. We used this dataset to train a novel vision-language model, which is, to the best of our knowledge, the first of its kind for GUI retrieval. We evaluated our approach on various datasets from related work and in a manual experiment. The results demonstrate that our model outperforms previous approaches in text-to-GUI retrieval achieving a Recall@10 of up to 0.69 and a HIT@10 of 0.91. We also explored the performance of GUIClip for other GUI tasks including GUI classification and sketch-to-GUI retrieval with encouraging results.

Eric H. Frater, Chris Seckar, J. Wedmore et al.

SPHEREx is a Medium Explorer astrophysics mission that requires a wide-field cryogenic short-wave infrared (SWIR) to mid-wave infrared (MWIR) telescope. The SPHEREx telescope has been designed and built at Ball Aerospace based on a JPL optical prescription and system architecture. The telescope has a 20cm entrance pupil, three freeform aluminum mirrors, a dichroic beam splitter furnished by Caltech, and forms two images in the SWIR and MWIR spectral bands. The “all-aluminum” architecture combined with a cryogenic space environment defines the opto-mechanical design approach for this system. Ball Aerospace performed developmental testing on a flight-like aluminum engineering development mirror for cryogenic surface figure and measured the differential thermal expansion of structural and optical aluminum materials. These development tests validated aspects of the athermal design prior to system-level integration and test. The telescope alignment process uses a laser tracker and system wavefront error (WFE) data to determine the adjustment of two mirrors and a focal plane assembly optical simulator (FPAOS). The FPAOS provides a retroreflection of interferometer light from each image location and an athermal focus position. The FPAOS was used in place of the SWIR band focal plane during system alignment and was moved to the MWIR focal plane interface to validate WFE performance in both bands. A cryogenic system WFE test was conducted to validate SWIR band performance at operational temperatures, and a post-vibrational WFE test demonstrates flight readiness. The SPHEREx telescope has been tested, delivered, and is ready for the next level of system integration.

Oliver Karras, Felix Wernlein, Jil Klünder et al.

[Background.] Empirical research in requirements engineering (RE) is a constantly evolving topic, with a growing number of publications. Several papers address this topic using literature reviews to provide a snapshot of its "current" state and evolution. However, these papers have never built on or updated earlier ones, resulting in overlap and redundancy. The underlying problem is the unavailability of data from earlier works. Researchers need technical infrastructures to conduct sustainable literature reviews. [Aims.] We examine the use of the Open Research Knowledge Graph (ORKG) as such an infrastructure to build and publish an initial Knowledge Graph of Empirical research in RE (KG-EmpiRE) whose data is openly available. Our long-term goal is to continuously maintain KG-EmpiRE with the research community to synthesize a comprehensive, up-to-date, and long-term available overview of the state and evolution of empirical research in RE. [Method.] We conduct a literature review using the ORKG to build and publish KG-EmpiRE which we evaluate against competency questions derived from a published vision of empirical research in software (requirements) engineering for 2020 - 2025. [Results.] From 570 papers of the IEEE International Requirements Engineering Conference (2000 - 2022), we extract and analyze data on the reported empirical research and answer 16 out of 77 competency questions. These answers show a positive development towards the vision, but also the need for future improvements. [Conclusions.] The ORKG is a ready-to-use and advanced infrastructure to organize data from literature reviews as knowledge graphs. The resulting knowledge graphs make the data openly available and maintainable by research communities, enabling sustainable literature reviews.

Zhiyu Fan, Yannic Noller, Ashish Dandekar et al.

The growing number of students enrolling in Computer Science (CS) programmes is pushing CS educators to their limits. This poses significant challenges to computing education, particularly the teaching of introductory programming and advanced software engineering (SE) courses. First-year programming courses often face overwhelming enrollments, including interdisciplinary students who are not CS majors. The high teacher-to-student ratio makes it challenging to provide timely and high-quality feedback. Meanwhile, software engineering education comes with inherent difficulties like acquiring industry partners and the dilemma that such software projects are often under or over-specified and one-time efforts within one team or one course. To address these challenges, we designed a novel foundational SE course. This SE course envisions building a full-fledged Intelligent Tutoring System (ITS) of Programming Assignments to provide automated, real-time feedback for novice students in programming courses over multiple years. Each year, SE students contribute to specific short-running SE projects that improve the existing ITS implementation, while at the same time, we can deploy the ITS for usage by students for learning programming. This project setup builds awareness among SE students about their contribution to a "to-be-deployed" software project. In this multi-year teaching effort, we have incrementally built an ITS that is now deployed in various programming courses. This paper discusses the Intelligent Tutoring System architecture, our teaching concept in the SE course, our experience with the built ITS, and our view of future computing education.

H. Ghaebi, Towhid Parikhani, Hadi Rostamzadeh et al.

Alirıza Altınsoy, Y. Arslan

Polyoxymethylene is used as an engineering material in many fields such as aircraft, aviation, and automotive industries in today due to its thermal resistance and mechanical properties. In this study, it is aimed to investigate the effects on the mechanical and structural properties of polyoxymethylene copolymer (POM-C) materials, which are used in many different industrial applications, by applying cryogenic treatment. For this purpose, deep cryogenic treatment was applied to the prepared samples at −175°C for 6, 12, 18, and 24 h, and then tensile, abrasion, impact, and hardness tests were applied to the samples that were kept at room temperature. In order to understand the changes in micro and crystal structures, XRD (X-Ray Diffraction), SEM (Scanning Electron Microscope), and FTIR (Fourier Transform Infrared Radiation) analyzes were performed, and based on these analyzes, the differences in the structure of the POM-C material were compared. It was observed that there was no improvement in the tensile strength of the deep cryogenically treated samples, but an increase in hardness and impact strength was detected.

A. Tikhonov

Until recently, the high rates of aircraft engine engineering’s development were ensured by the technological solutions improvement and the desire to approximate as much as possible the ideal thermodynamic cycle of turbojet engines. The traditional fuel for turbojet engines is an aviation kerosene – Jet-A fuel group and their regional analogies. The traditional way of aircraft engines efficiency increasing is a raising of a temperature in front of the high-pressure turbine. New alloys and technologies allow to increase the aircraft engines efficiency to a certain level. Raising the temperature in the combustion chamber by 50 degrees increases the efficiency, which leads to a 5% reduction in fuel consumption. However, this approach is technology limited and does not provide innovative solutions. The aircraft engine engineering’s development tempo in the 21st century continues to accelerate. The main driver of such processes in recent years is the tightening of economic and environmental requirements. Many aircraft manufacturers are actively looking for ways to reach a new qualitative level in terms of turbojet engines economic efficiency and meeting strict environmental requirements. The paper considers the feasibility of using new cryogenic fuels in aircraft turbojet engines, and possible ways for aircraft industry successful development.

Praveen Alok, Debjyoti Sahu

The present paper reports the performance of a popular refrigerant R32 (Difluoromethane, CF2H2) experiencing the two phase injection process. Two phase injection process may lower the discharge temperature of a multistage compressor. In order to investigate the role and impact of two-phase injection on a compressor, a Scroll compressor is selected because scroll compressor has high tolerance for liquid refrigerant. A reputed compressor is chosen where all the operating conditions and specifications are available in public domain. The modelling and analysis of refrigeration system is carried out using a simple MATLAB code. Around 200 iterations were performed for four different condensing and evaporating temperatures. The maximum reduction in discharge temperature is found to be 44°C when compared to R410A used in the same system. Cite this article as: Praveen A, Debjyoti S. Numerical analysis of a two-phase injection refrigeration cycle using R32. J Ther Eng 2022;8(2):157–168. Journal of Thermal Engineering Web page info: https://jten.yildiz.edu.tr DOI: 10.18186/thermal.1077857