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

Dr.A.Kishore Kumar, Ram Manohar Pandey, Dr.Anjani Kumar Singh

Abstract: Inconel 718 is a precipitation-hardened nickel-based superalloy extensively used in aerospace, power generation, and high-temperature engineering applications due to its exceptional mechanical strength, corrosion resistance, and stability at elevated temperatures. Despite these superior properties, the alloy is widely recognized as one of the most difficult-to-machine materials. Its low thermal conductivity, high work-hardening tendency, strong chemical affinity with cutting tools, and ability to retain high strength at elevated temperatures collectively lead to rapid tool wear, high cutting forces, and poor surface integrity during machining operations. Consequently, improving the machinability of Inconel 718 has become a significant research focus in modern manufacturing science. This review paper presents a comprehensive overview of the machinability characteristics of Inconel 718 by systematically analyzing the fundamental challenges, tool wear mechanisms, machining performance indicators, and recent technological advancements reported in the literature. The review first discusses the intrinsic material properties of Inconel 718 that influence its machining behavior, including microstructural characteristics, strain hardening behavior, and thermal properties. Particular attention is given to the role of these properties in influencing cutting temperature, chip morphology, and tool–workpiece interaction. Subsequently, the study examines the performance of different cutting tool materials such as coated carbides, ceramics, cubic boron nitride (CBN), and polycrystalline diamond (PCD), highlighting their advantages and limitations in high-temperature machining environments. Various tool wear mechanisms including abrasion, adhesion, diffusion, oxidation, and notch wear are critically analyzed to understand the degradation of tool life during machining processes. Furthermore, the paper reviews the influence of key machining parameters such as cutting speed, feed rate, and depth of cut on machinability indicators including cutting forces, surface roughness, tool life, and chip formation. Advanced cooling and lubrication techniques such as cryogenic cooling, minimum quantity lubrication (MQL), and hybrid cooling approaches are also discussed, emphasizing their role in reducing thermal loads and enhancing machining efficiency. In addition, the application of advanced machining processes including electrical discharge machining (EDM), wire EDM, laser-assisted machining, and hybrid machining techniques is explored as alternative approaches for improving the machinability of Inconel 718. The review also highlights recent developments in process optimization, modeling, and simulation techniques that have been employed to predict machining performance and optimize cutting conditions. These include numerical simulations, finite element modeling, and data-driven approaches such as artificial intelligence and machine learning for intelligent manufacturing. Finally, the study identifies critical research gaps and proposes future directions for enhancing machinability through innovative tool design, sustainable cooling strategies, and advanced manufacturing technologies. Overall, this review provides a consolidated understanding of the machining behavior of Inconel 718 and offers valuable insights for researchers and industry professionals seeking to improve machining performance and productivity in high-temperature alloy manufacturing. Keywords: Machinability; Inconel 718; Nickel-based superalloy; Tool wear mechanisms; Surface integrity; Cutting parameters; Cooling and lubrication techniques; Advanced machining processes.

Vo Van Tai, Truong Van Tuan, Tran Trong Tai et al.

We theoretically study the thermoelectric transport S in a double-layer bilayer graphene (BLG-GaAs-BLG) system on dielectric substrates (h-BN, Al2O3, HfO2). Electrons interact with GaAs acoustic phonons via both the deformation potential (acDP) and piezoelectric (acPE) scattering. Results show that piezoelectric scattering dominates the total transport, especially at low carrier density and high dielectric constant. Substrate dielectric constant significantly influences thermopower S, and the thermopower of the materials is in the order of HfO2>Al2O3>h-BN. When densities on two BLG layers are unequal, the contribution from acDP scattering Sd decreases (increases) at low (high) densities versus equal densities, while acPE scattering Sg remains stable, making S largely Sg-dependent. Increasing interlayer distance d enhances S, while higher temperature boosts Sd (notably at low densities) with minimal effect on Sg. These insights and substrate-dependent trends demonstrate substrate engineering as a key parameter for optimizing BLG thermoelectric devices

R. Kalla, A. Garva, P. Ghosh

A water hammer is a pressure surge caused by the sudden stoppage of a moving liquid, typically due to rapid valve closure or pump shutdown. This abrupt momentum change generates a powerful pressure wave that can damage pipes and reduce component efficiency. If the pressure drops below the liquid vapor pressure, vapor cavities form and collapse under high localized pressure, causing cavitation. In cryogenic fluids, water hammer becomes more complex due to unique thermophysical properties at low temperatures. The thermal suppression effect reduces localized vapor pressure, making cavitation harder and altering pressure wave dynamics compared to non-cryogenic fluids. Understanding and predicting these dynamics are vital for optimizing engineering systems, and numerical modeling aids in this effort. In cryogenic fluids, water hammer becomes more complex due to unique thermophysical properties at low temperatures. The thermal suppression effect reduces localized vapor pressure, making cavitation harder and altering pressure wave dynamics compared to non-cryogenic fluids. Understanding and predicting these dynamics are important for optimizing engineering systems, and numerical modelling is employed to predict and understand this intricate behaviour. The study employs a Finite Volume Method (FVM) to analyze water hammer, starting with water as a baseline due to its well-defined properties and experimental data. The model is then adapted for cryogenic fluids to capture their distinct behavior, validated against available experimental data to ensure accuracy.

Shalini Chakraborty, Sebastian Baltes

The IT industry provides supportive pathways such as returnship programs, coding boot camps, and buddy systems for women re-entering their job after a career break. Academia, however, offers limited opportunities to motivate women to return. We propose a diverse multicultural research project investigating the challenges faced by women with software engineering (SE) backgrounds re-entering academia or related research roles after a career break. Career disruptions due to pregnancy, immigration status, or lack of flexible work options can significantly impact women's career progress, creating barriers for returning as lecturers, professors, or senior researchers. Although many companies promote gender diversity policies, such measures are less prominent and often under-recognized within academic institutions. Our goal is to explore the specific challenges women encounter when re-entering academic roles compared to industry roles; to understand the institutional perspective, including a comparative analysis of existing policies and opportunities in different countries for women to return to the field; and finally, to provide recommendations that support transparent hiring practices. The research project will be carried out in multiple universities and in multiple countries to capture the diverse challenges and policies that vary by location.

Mia Mohammad Imran, Tarannum Shaila Zaman

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the \textbf{Operationalization for LLM-based Annotation Framework (OLAF)}, a conceptual framework that organizes key constructs: \textit{reliability, calibration, drift, consensus, aggregation}, and \textit{transparency}. The paper aims to motivate methodological discussion and future empirical work toward more transparent and reproducible LLM-based annotation in software engineering research.

V. Tarenkov, V. Krivoruchko, A. Shapovalov et al.

Recently, severe plastic deformation engineering has emerged as a powerful tool to control the main mechanical properties of metals and alloys. In particular, it concerns the high-pressure torsion method where the material is torsionally strained under high pressure between two anvils. It has been found that the reduction in crystallinity of metallic materials by the shear strain in combination with their nanostructuring results in an inherent high strength together with low-temperature superplasticity or improved creep resistance. In this work, using the point-contact spectroscopy technique, we analyze how the local superconducting characteristics of a Mo-Re alloy are modified after high-pressure torsion processing. We record the restoration of suppressed superconductivity on the surface of the samples, a significant strengthening of the electron-phonon coupling in them, and a slight increase in the superconducting transition temperature. The obtained results are explained based on modern concepts about the decisive influence of phonon softening on the basic properties of intrinsically disordered superconductors.

A. Sauleyeva, Y. Korshikov, K. Turlybekuly et al.

This article presents a comprehensive set of experimental and computational methods aimed at determining heat transfer regimes in superfluid helium-4, evaluating thermal resistance at various temperatures, and developing a scalable model for analyzing the performance of an ultracold neutron (UCN) converter. The results obtained constitute an essential part of the scientific foundation required for the development and optimization of modern UCN sources, which operate on the principle of neutron thermalization through inelastic interactions with the medium. This study is fundamental in nature and is oriented toward addressing strategically important problems in neutron physics, such as refining the neutron lifetime and searching for the neutron electric dipole moment. These challenges are crucial for advancing our understanding of nucleosynthesis and the formation of matter in the early Universe. The advancement of heat transfer models in cryogenic environments, particularly in superfluid helium, plays a key role in ensuring the stability and efficiency of UCN sources. The paper discusses approaches to the metrological verification of thermal parameters and provides recommendations for applying the results in future engineering and design developments.

Jinzhen Wang, Baohua Chao, Sihao Liu et al.

A helium refrigerator utilizing a turbine Brayton refrigerator instead of liquid nitrogen is proposed as the pre-cooling stage, and a thermodynamic system cycle flow is built up. Turbine Brayton refrigeration has the advantages of high efficiency, low maintenance costs, no free, and low noise. When applied in the pre-cooling stage of helium refrigerators, it can avoid the continuous supply of liquid nitrogen and improve the adaptability of helium refrigerators. We utilize genetic algorithms for component optimization and conduct thermodynamic research on the system under design conditions. The results indicate that the proposed system has better cyclic performance and can provide a reference and basis for practical engineering applications.

G. Mahendran, R. Ramadoss, C. Rajendran et al.

Chunmei Guo, Yuxin Hao, Botao Gou

Abstract Evaporative condensing chillers have been widely used in rail transit, data centers, communication base stations and other fields, but the simulation of evaporative condensing chillers has not yet reached the stage of engineering design and application. Therefore, based on the DOE-2 model of the general chiller, considering that the energy efficiency of the evaporative condensing chillers is related to the inlet air wet bulb temperature, it is used to replace the inlet cooling water temperature, and the evaporative condensing chillers model is established. The evaporative condensing chillers model was combined with TRNSYS to develop an evaporative condensing chillers module that includes condensing fans and cooling water pumps using C++ compilation algorithm program. This module was used to simulate a subway station in Tianjin City. The results showed that the average coefficient of performance of the evaporative condensing refrigeration system during operation was 5.68, and the average system coefficient of performance was 4.76. To our knowledge, it is the first time proposed the evaporative condensing chillers energy simulation module and related the outlet chilled water temperature and the inlet air wet bulb temperature to refrigerating capacity as well. The development of the module provides convenience for the study and optimizes evaporative condensing chillers performance.

Salam A. Hashim, M. R. Hasan, Ayad M. Al Jubori

This work aims to evaluate the effect of compressor inlet air temperature on the power cycle performance of gas turbines, employing different control operation techniques. Therefore the power cycle of the combination of a Gas Turbine (GT) with a single effect H2O-BrLi absorption refrigeration is examined. GT power cycle simulations are carried out based on the full and partial load model of power and cooling systems, deploying the Thermo-flow and Engineering Equation Solver (EES). Moreover, Turbine Inlet Temperature (TIT), Inlet Guide Vane (IGV), and the combined IGV and TIT control strategies, are employed to evaluate the advantages of applying various GT power cycles and off-design operations. The results exhibit that the combined IGV and TIT method is the appropriate one, offering higher integrated cooling and power system efficiency compared to the TIT control approach alone. When the compressor intake air temperature rises, it negatively influences cycle effectiveness. The air mass flow rate and pressure ratio decrease, thus, leading to a decrease in the power output and thermal efficiency of the gas turbine. Finally, the absorption cooling system implementation improves power generation and thermal efficiency in a GT power plant, by 20.68% and 5.32%, respectively.

Abdul Khaliq, Rajesh Kumar, T. Al‐Mughanam et al.

This study devised a novel cooling-power cogeneration system utilizes parabolic trough collector (PTC) employing Air, CO2, He as heat carrying fluids, and Organic flash cycle (OFC) connected to two-phase ejector for simultaneously generating the electricity, and cooling for refrigeration and air conditioning. Modelling & simulation through Engineering Equation Solver (EES) is performed to investigate the effect of solar flux, and type of solar heat transfer fluid (SHTF) on exit temperature of SHTF. Promotion of solar flux increases the temperature of SHTF which is found highest for He and lowest for CO2. A parametric analysis is done to find out the outcome change of design parameters. Cogeneration cycle connected to He operated PTC performs good relative to Air and CO2 as SHTF. Exergy destruction is found to be 53.87 %, 22.09 %, and 6.15 % in PTC, OFC, and in two-phase ejector respectively while production of power, exergetic refrigeration, & exergetic air-conditioning as 4.02 %, 10.65 %, 3.22 % respectively.

T. Al‐Mughanam, Abdul Khaliq

A gaseous flow is employed as heat transfer fluid (HTF) in a parabolic trough solar collector (PTSC) for simultaneous production of cooling at three different levels of temperature to meet the demands of air conditioning, refrigeration, and ultra-low temperature refrigeration required to ensure the efficacy of some special vaccines. The combined system consists of five subsystems including PTSC, Kalina cycle, ejector refrigeration cycle (ERC), cascaded refrigeration cycle (CRC), and absorption refrigeration cycle (ARC). A simulation through Engineering Equation Solver (EES) is conducted to assess the impact of internal tube diameter of absorber and solar irradiation on rise of HTF temperature and mass flow rate of Kalina cycle fluid. It is determined that for given solar irradiation, temperature of HTF goes down when internal diameter of absorber tube is enlarged. The influence of weather conditions; solar irradiation and ambient temperature, type of HTF, and concentration of ammonia-water basic solution on thermal and exergy efficiencies of three-stage cooling cycle (TSC) are examined. The TSC with helium operated PTSC deliver better results than air and CO2. Exergy analysis show that solar collector (30.26%) dissipates the highest exergy, followed by ejector (12.5%) and VGSS (7.61%). Type of CRC fluid-pair affect TSC cycle refrigeration capacity, and cooling exergy efficiency. Promotion of solar irradiation from 850 to 1200 W/m2 increases the cooling exergy efficiency of three-stage cycle from 6.72% to 9.52% when evaporator temperature is set at −45°C and CRC employs NH3-propylene.

Yang Shihao, Qian Xiaoshi

Electrocaloric cooling is a solid-state cooling technique based on the manipulation of electric fields. This technology utilizes the temperature variations induced in electrocaloric materials under the influence of an electric field to achieve refrigeration effects. Owing to its advantages, such as zero direct carbon emissions and high efficiency, it has garnered widespread attention, particularly in the context of global warming and carbon reduction objectives. Since the discovery of the giant electrocaloric effect in 2006, electrocaloric cooling technology has undergone rapid development, particularly in improvements in electrocaloric materials and devices. This article provides an analysis and discussion focused on electrocaloric cooling device research, electrocaloric polymer nanocomposite materials, and high-entropy optimization of electrocaloric materials. It commences by introducing the fundamental principles of the electrocaloric effect and current advancements in active regenerative electrocaloriccooling devices. Subsequently, it summarizes the progress in electrocaloric polymer nanocomposite materials, along with strategies for high-entropy optimization and interface polarization enhancement. Finally, it provides insights into future research directions for electrocaloric cooling within the fields of working substances and systems.

Li Jing, Liu Qingshan, Yang Peng et al.

Stirling cryocoolers have the advantages of fewer moving parts, oil-free, single-phase heat transfer, a large refrigeration temperature range, convenient and adjustable refrigeration capacity, and high refrigeration efficiency. Therefore, they have broad application prospects in commercial and domestic refrigeration systems. To meet the demands of low-temperature refrigerators, this study developed a multi-temperature zone refrigerator with a vapor compression refrigeration system and a Stirling cryocooler. The performance of the Stirling cryocooler was tested. The designs of the heat dissipation and cooling conduction structures were optimized, and the refrigerator’s overall performance was examined. Moreover, the influences of input power and ambient temperature on the performance of the Stirling cryocooler were investigated. The results showed that the cooling output and coefficient of performance (COP) of the Stirling cryocooler increased with an increase in the cold-end temperature, and increasing the input power provided a higher cooling capacity but decreased the COP. Under an ambient temperature of 43 °C, the cooling capacity of the Stirling cryocooler was 28.97 W with a COP of 0.37 when the cold-end temperature was -60 °C. Heat transfer structures at the cold and hot ends of the Stirling cryocooler based on heat-pipe technology were also proposed, and the simulation showed that the proposed structures for heat dissipation and cooling conduction met the system design requirements. Finally, an experimental test of refrigerator performance was conducted. A no-load experiment at an ambient temperature of 32 °C showed that the pull-down time of the low-temperature room was 28% shorter than that of the freezer room. Under an ambient temperature of 43 °C, the low-temperature room reached an average temperature of -64.5 °C, and the power consumptions of the Stirling cryocooler and refrigerator were 2.33 kW?h/d and 4.13 kW?h/d, respectively.

Isaiah Lahr, Saghir Alfasly, Peyman Nejat et al.

Searching for similar images in archives of histology and histopathology images is a crucial task that may aid in patient matching for various purposes, ranging from triaging and diagnosis to prognosis and prediction. Whole slide images (WSIs) are highly detailed digital representations of tissue specimens mounted on glass slides. Matching WSI to WSI can serve as the critical method for patient matching. In this paper, we report extensive analysis and validation of four search methods bag of visual words (BoVW), Yottixel, SISH, RetCCL, and some of their potential variants. We analyze their algorithms and structures and assess their performance. For this evaluation, we utilized four internal datasets ($1269$ patients) and three public datasets ($1207$ patients), totaling more than $200,000$ patches from $38$ different classes/subtypes across five primary sites. Certain search engines, for example, BoVW, exhibit notable efficiency and speed but suffer from low accuracy. Conversely, search engines like Yottixel demonstrate efficiency and speed, providing moderately accurate results. Recent proposals, including SISH, display inefficiency and yield inconsistent outcomes, while alternatives like RetCCL prove inadequate in both accuracy and efficiency. Further research is imperative to address the dual aspects of accuracy and minimal storage requirements in histopathological image search.

Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco et al.

Software engineering (SE) activities have been revolutionized by the advent of pre-trained models (PTMs), defined as large machine learning (ML) models that can be fine-tuned to perform specific SE tasks. However, users with limited expertise may need help to select the appropriate model for their current task. To tackle the issue, the Hugging Face (HF) platform simplifies the use of PTMs by collecting, storing, and curating several models. Nevertheless, the platform currently lacks a comprehensive categorization of PTMs designed specifically for SE, i.e., the existing tags are more suited to generic ML categories. This paper introduces an approach to address this gap by enabling the automatic classification of PTMs for SE tasks. First, we utilize a public dump of HF to extract PTMs information, including model documentation and associated tags. Then, we employ a semi-automated method to identify SE tasks and their corresponding PTMs from existing literature. The approach involves creating an initial mapping between HF tags and specific SE tasks, using a similarity-based strategy to identify PTMs with relevant tags. The evaluation shows that model cards are informative enough to classify PTMs considering the pipeline tag. Moreover, we provide a mapping between SE tasks and stored PTMs by relying on model names.

Johannes Schleiss, Aditya Johri

In this practice paper, we propose a framework for integrating AI into disciplinary engineering courses and curricula. The use of AI within engineering is an emerging but growing area and the knowledge, skills, and abilities (KSAs) associated with it are novel and dynamic. This makes it challenging for faculty who are looking to incorporate AI within their courses to create a mental map of how to tackle this challenge. In this paper, we advance a role-based conception of competencies to assist disciplinary faculty with identifying and implementing AI competencies within engineering curricula. We draw on prior work related to AI literacy and competencies and on emerging research on the use of AI in engineering. To illustrate the use of the framework, we provide two exemplary cases. We discuss the challenges in implementing the framework and emphasize the need for an embedded approach where AI concerns are integrated across multiple courses throughout the degree program, especially for teaching responsible and ethical AI development and use.

Bohui Zhang, Valentina Anita Carriero, Katrin Schreiberhuber et al.

Ontology engineering (OE) in large projects poses a number of challenges arising from the heterogeneous backgrounds of the various stakeholders, domain experts, and their complex interactions with ontology designers. This multi-party interaction often creates systematic ambiguities and biases from the elicitation of ontology requirements, which directly affect the design, evaluation and may jeopardise the target reuse. Meanwhile, current OE methodologies strongly rely on manual activities (e.g., interviews, discussion pages). After collecting evidence on the most crucial OE activities, we introduce \textbf{OntoChat}, a framework for conversational ontology engineering that supports requirement elicitation, analysis, and testing. By interacting with a conversational agent, users can steer the creation of user stories and the extraction of competency questions, while receiving computational support to analyse the overall requirements and test early versions of the resulting ontologies. We evaluate OntoChat by replicating the engineering of the Music Meta Ontology, and collecting preliminary metrics on the effectiveness of each component from users. We release all code at https://github.com/King-s-Knowledge-Graph-Lab/OntoChat.

Li Jinbo, Zhao Fufeng, Li Rixin et al.

Based on a three-dimensional distributed parameter model, a simulation model of a small-diameter heat exchanger in the indoor unit of a split-household air-conditioner was established, and the performance metrics were computed, including the total heat load, sensible heat load, latent heat load, refrigerant-side pressure drop, and air-side pressure drop. The effects of the tube length, refrigerant mass flow rate, air volumetric flow rate, air inlet temperature, and air inlet relative humidity on the heat exchanger performance metrics were determined under different working conditions. For the 5 mm diameter heat exchanger considered in this study, the corresponding tube length range was 0.6~0.7 m, achieving good heat transfer with a small pressure drop. Owing to the comprehensive influence of the heat transfer coefficient and the effective mass transfer time, when the volumetric flow of air was in the range of 600–700 m3/h, the latent heat load reached a maximum of 426 W. With an increase in the air inlet temperature, the sensible heat load first increased and then decreased.