CIRP Journal of Manufacturing Science and Technology最新文献_第2页

A new characterization methodology for assessing machinability through cutting energy consumption 通过切削能耗评估加工性能的新表征方法

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-19 DOI: 10.1016/j.cirpj.2024.10.008

Kai Ma , Zhanqiang Liu , Bing Wang , Delin Liu

Improving machinability has consistently been an essential research topic in the machining community. However, a rapid and effective method to characterize machinability from the fundamental essence of machining is still lacking. This work proposed a new characterization methodology for assessing machinability from the principle of cutting energy consumption. An original Drop Hammer based Orthogonal Cutting (DHOC) test machine driven by gravitational potential energy was developed to conduct the machinability test. Using the Cutting Distance with Equal Energy (CDEE) method, machinability can be assessed by measuring the cutting distance without expensive measuring apparatus. Therefore, the cutting distance indicator can simplify the test procedure. Meanwhile, the CDEE method avoids the necessity for precisely calculating the consumptions of various complex cutting energies. Moreover, in-situ measurements coupled with the Digital Image Correlation (DIC) technique and Electron Back-Scattered Diffraction (EBSD) characterizations were utilized to evaluate the deformation characteristics and surface integrity during the CDEE tests. The proposed CDEE method has been validated from three aspects involving materials, cutting tools, and surface modification technology. Furthermore, a machinability optimization procedure based on the CDEE method has been proposed. The cutting distance indicator was used as an optimization objective for optimizing technology parameters to improve machinability. This CDEE method based on the DHOC test machine proved to have high application potential for the characterization and optimization of machinability.

提高加工性能一直是机械加工领域的重要研究课题。然而，目前仍缺乏一种快速有效的方法，从机械加工的根本本质出发来表征机械加工性能。这项工作提出了一种从切削能耗原理评估加工性能的新表征方法。为了进行加工性测试，我们开发了一种由重力势能驱动的基于落锤正交切削（DHOC）试验机。使用等能量切割距离（CDEE）方法，无需昂贵的测量仪器，只需测量切割距离即可评估可加工性。因此，切削距离指示器可以简化测试程序。同时，CDEE 方法避免了精确计算各种复杂切削能量消耗的必要性。此外，在 CDEE 试验过程中，还利用原位测量、数字图像相关（DIC）技术和电子背散射衍射（EBSD）特性来评估变形特征和表面完整性。从材料、切削工具和表面改性技术三个方面对所提出的 CDEE 方法进行了验证。此外，还提出了基于 CDEE 方法的可加工性优化程序。切削距离指标被用作优化技术参数以提高加工性能的优化目标。事实证明，这种基于 DHOC 试验机的 CDEE 方法在表征和优化加工性能方面具有很大的应用潜力。

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引用次数: 0

Layer-level fabrication of continuous functionally graded materials (cFGMs) via Powder Bed Fusion – Laser Beam technology 通过粉末床熔融-激光束技术在层级上制造连续功能分级材料 (cFGM)

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-19 DOI: 10.1016/j.cirpj.2024.10.009

Paolo Posa , Vito Errico , Andrea Angelastro, Sabina Luisa Campanelli

Multi-material fabrication of metals through Additive Manufacturing (AM) processes is attracting more and more attention in recent years. This work presents a novel methodology that enables the fabrication of continuous functionally graded materials (cFGMs) at the layer level using Powder Bed Fusion – Laser Beam (PBF-LB) technology. This has been achieved by designing and building a customized powder separation system that can be easily installed on a currently operating PBF-LB system with a blade/roller-based powder spreading technique (extremely limited for layer-level multi-material fabrication). This technique overcomes one of the main drawbacks of AM multi-material fabrication by properly joining materials with very different mechanical properties and low compatibility, thus extending the productive capacity of this technology. Two steels, AISI 316 L and 18 Ni Maraging 300, with different physical, chemical and mechanical properties, were used to study the applicability and verify the proposed methodology. A high-resolution optical system was used to monitor, layer by layer, the different laser-matter interactions given by the different materials and thus the presence of a graded transition zone between them. Results in terms of statical mechanical properties, microstructure, chemical analysis and optical monitoring showed that the proposed solution is reliable and cost-effective, paving the way for future applications.

近年来，通过增材制造（AM）工艺进行金属的多材料制造正吸引着越来越多的关注。本研究提出了一种新方法，可利用粉末床熔融-激光束（PBF-LB）技术在层级上制造连续功能分级材料（cFGMs）。这是通过设计和建造一个定制的粉末分离系统实现的，该系统可轻松安装在当前运行的 PBF-LB 系统上，并采用基于刀片/滚筒的粉末铺展技术（对于层级多材料制造而言极为有限）。该技术克服了 AM 多材料制造的一个主要缺点，即可以将机械性能迥异、兼容性低的材料适当连接起来，从而提高了该技术的生产能力。我们使用了两种具有不同物理、化学和机械性能的钢材（AISI 316 L 和 18 Ni 马氏体 300）来研究拟议方法的适用性并进行验证。使用高分辨率光学系统逐层监测不同材料产生的不同激光-物质相互作用，从而监测它们之间是否存在分级过渡区。在静态机械性能、微观结构、化学分析和光学监测方面的结果表明，所提出的解决方案既可靠又具有成本效益，为今后的应用铺平了道路。

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引用次数: 0

Assessment of cutting force coefficient identification methods and force models for variable pitch and helix bull-nose tools 评估可变螺距和螺旋牛鼻子刀具的切削力系数识别方法和力模型

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-15 DOI: 10.1016/j.cirpj.2024.09.010

Joshua Priest , Sabino Ayvar-Soberanis , Javier Dominguez-Caballero , Peace Onawumi , Zekai Murat Kilic , David Curtis

The mechanistic approach is commonly implemented to predict and optimise the cutting forces in milling processes to prevent tool breakages, reduce tool wear, reduce form error, and improve surface quality. To implement this method, the cutting force coefficients (CFCs), that characterise the mechanics of the process, must be calculated. This study compares the accuracy of the predicted cutting forces for variable pitch and helix bull-nose milling tools using a rapid testing (RT) optimisation-based mechanistic CFC identification method that only requires a single angular cut with increasing radial engagement to the traditional mechanistic approach that requires several straight cuts. Along with developing a hybrid technique that combines variation in feed rate and radial engagement. The traditional radial, tangential, and axial (RTA) force model is also compared with the frictional and normal rake face (UV) force model that is independent of the local tool rake and inclination angles which is a necessary for bull nose tools. The RT and the developed hybrid CFC identification method with the UV force model predicted the average

F_{x}

,

F_{y}

and

F_{z}

cutting forces to within 7.1 %, 4.3 %, and 3.8 % error, respectively. These methods were slightly less accurate than the traditional method, however they have significant industrial benefits because they have can be used to identify CFCs with either a single cut, or from any tool-path with chip-load variation, respectively. The RTA force model predicted the average cutting forces similarly to the UV force model, however, the UV force model had lower errors using the rapid RT testing method at the extreme corners of the experimental design space.

机械方法通常用于预测和优化铣削过程中的切削力，以防止刀具破损、减少刀具磨损、降低形状误差并提高表面质量。要实施这种方法，必须计算切削力系数（CFCs），这是加工过程的力学特征。本研究使用基于快速测试（RT）优化的机械 CFC 识别方法，对可变螺距和螺旋牛鼻铣刀的切削力预测精度进行了比较，该方法只需要一次角度切削，并增加径向啮合，而传统的机械方法则需要多次直切削。同时还开发了一种混合技术，将进给量和径向啮合的变化结合起来。传统的径向、切向和轴向（RTA）力模型也与摩擦力和法向斜面（UV）力模型进行了比较，后者与牛鼻子刀具所需的局部刀具斜面和倾斜角无关。RT 和开发的混合 CFC 识别方法与 UV 力模型预测的平均 Fx、Fy 和 Fz 切削力误差分别在 7.1%、4.3% 和 3.8% 以内。这些方法的精确度略低于传统方法，但它们具有显著的工业效益，因为它们可分别用于识别单次切削或任何刀具路径的切屑载荷变化的氯氟化碳。RTA 力模型对平均切削力的预测与 UV 力模型相似，但在实验设计空间的极端角落，使用快速 RT 测试方法，UV 力模型的误差更小。

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引用次数: 0

Worker-centered evaluation and redesign of manufacturing tasks for ergonomics improvement using axiomatic design principles 以工人为中心，利用公理设计原则对生产任务进行评估和重新设计，以改善工效学

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-11 DOI: 10.1016/j.cirpj.2024.10.001

Z. Arkouli, G. Michalos, G. Kokotinis, S. Makris

Humans are considered the most valuable resource in manufacturing systems thanks to their craftsmanship, dexterity, and autonomy significantly affecting productivity, quality, and the overall company competitiveness. This paper introduces the SAGE (Systematic Approach to Generating Ergonomic Manufacturing tasks) methodology, a structured approach based on Axiomatic Design principles to integrate Human Factors evaluation early in the operations design phase and redesign manufacturing tasks to improve operators well-being. The primary objective is to mitigate discomfort and safety risks that often lead to musculoskeletal disorders, absenteeism, and production delays. SAGE provides a comprehensive framework for assessing ergonomic aspects of manufacturing tasks and identifying the need for redesign. It offers a detailed set of Functional Requirements (FRs) for reference, assesses FR satisfaction, evaluates task complexity using the Independence Axiom, and examines the intensity of FR satisfaction through the Information Axiom. The methodology includes specific implementation guidelines, ensuring its applicability across diverse manufacturing contexts. Its effectiveness is demonstrated through a large-scale parts assembly case study inspired by the bus and coach industrial sector, where a production engineer evaluated a windows assembly task and identified ergonomic design interventions. A comparative analysis with other relevant methods is finally presented, highlighting the approach's effectiveness.

人被认为是制造系统中最宝贵的资源，因为他们的手工艺、灵巧性和自主性对生产率、质量和公司整体竞争力有着重大影响。本文介绍了 SAGE（生成符合人体工程学的制造任务的系统方法）方法，这是一种基于公理设计原则的结构化方法，用于在操作设计阶段早期整合人因评估，并重新设计制造任务，以改善操作员的福祉。其主要目的是减轻经常导致肌肉骨骼疾病、旷工和生产延误的不适感和安全风险。SAGE 提供了一个全面的框架，用于评估生产任务的人体工程学方面，并确定重新设计的必要性。它提供了一套详细的功能要求（FR）供参考，评估功能要求的满意度，使用独立性公理评估任务的复杂性，并通过信息公理检查功能要求满意度的强度。该方法包括具体的实施指南，确保其适用于各种制造环境。受公共汽车和长途客车工业部门的启发，该方法通过大规模零件装配案例研究证明了其有效性，在该案例研究中，一名生产工程师评估了窗口装配任务，并确定了符合人体工程学的设计干预措施。最后还介绍了与其他相关方法的比较分析，突出了该方法的有效性。

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引用次数: 0

Experimental evaluation of 5G performance based on a digital twin of a machine tool 基于机床数字孪生系统的 5G 性能实验评估

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-07 DOI: 10.1016/j.cirpj.2024.09.012

Jan Mertes , Christian Schellenberger , Li Yi , Marius Schmitz , Moritz Glatt , Matthias Klar , Bahram Ravani , Hans D. Schotten , Jan C. Aurich

The 5G mobile communication standard can potentially meet the networking requirements for different industrial use cases simultaneously due to the promised low latency, high bandwidth, and high device density while providing a high quality of service. These capabilities enable the realization of digital twins (DTs) that are based on edge computing for time- and safety-critical wireless applications. However, the investigation of the applicability of 5G for DTs in real-world manufacturing scenarios is still lacking. In this work, we have evaluated a DT based on edge-computing and 5G mobile communication using extensive experiments. We have focused on the communication technology and requirements needed to enable functionalities on edge devices. The key contribution of this paper is a comprehensive experimental study on 5G performance characteristics in an existing manufacturing system. Moreover, the influence of 5G on the functionality of the edge-based DT is evaluated and discussed. Full factorial experiments with different network configurations are designed and conducted. The performance of communication characteristics (latency, jitter) is evaluated as well as the impact on the continuity between real and digital processes. The results are also compared with the WiFi standard by experimental evaluation. At last, the limits of current 5G networks for manufacturing are discussed.

5G 移动通信标准具有低延迟、高带宽和高设备密度的特点，可同时满足不同工业用例的网络要求，并提供高质量的服务。这些功能使基于边缘计算的数字孪生（DT）得以实现，用于时间和安全关键型无线应用。然而，5G 在实际制造场景中对数字孪生的适用性还缺乏研究。在这项工作中，我们通过大量实验对基于边缘计算和 5G 移动通信的 DT 进行了评估。我们重点研究了实现边缘设备功能所需的通信技术和要求。本文的主要贡献在于对现有制造系统中的 5G 性能特征进行了全面的实验研究。此外，我们还评估并讨论了 5G 对基于边缘的 DT 功能的影响。本文设计并进行了不同网络配置的全因子实验。评估了通信特性（延迟、抖动）的性能以及对实际流程和数字流程之间连续性的影响。通过实验评估，还将结果与 WiFi 标准进行了比较。最后，讨论了当前 5G 网络在制造业中的局限性。

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引用次数: 0

Physics-supported Bayesian machine learning for chatter prediction with process damping in milling 利用物理贝叶斯机器学习预测铣削过程中的颤振和加工阻尼

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-04 DOI: 10.1016/j.cirpj.2024.09.014

Vahid Ostad Ali Akbari , Andrea Eichenberger , Konrad Wegener

Chatter stability of milling operations is a complicated phenomenon causing serious productivity issues in the manufacturing industry, yet a shop-floor implementable solution is lacking. This paper follows a physics-supported Bayesian machine learning approach and incorporates the potential effect of process damping on the stability of the process. Using a likelihood function based on the Nyquist stability criterion, the learning system monitors the actual stability state of the process during arbitrary cuts and refines the underlying model parameter uncertainties in the structural dynamics, cutting force coefficients, as well as the process damping. The framework can operate with limited training data and display the remaining uncertainties in stability predictions to the machine operator. Experimental case studies show the effectiveness of the proposed method and highlight the importance of considering process damping for certain endmills.

铣削操作中的颤振稳定性是一个复杂的现象，在制造业中造成了严重的生产率问题，但却缺乏一种可在车间实施的解决方案。本文采用物理支持的贝叶斯机器学习方法，并将加工阻尼对加工稳定性的潜在影响纳入其中。利用基于奈奎斯特稳定性准则的似然函数，学习系统监控任意切割过程中工艺的实际稳定性状态，并完善结构动力学、切割力系数以及工艺阻尼中的基础模型参数不确定性。该框架可在训练数据有限的情况下运行，并向机器操作员显示稳定性预测中的剩余不确定性。实验案例研究表明了所提方法的有效性，并强调了考虑某些立铣刀加工阻尼的重要性。

引用次数: 0

Numerical modelling and experimental investigations to predict the tool wear of copper electrodes during µ-EDM process 预测 µ-EDM 过程中铜电极工具磨损的数值建模和实验研究

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-04 DOI: 10.1016/j.cirpj.2024.09.011

S. Arun, M. Manikandan, Jino Joshy, Basil Kuriachen, Jose Mathew

The micro electrical discharge machining (µ-EDM) process is one of the most widely used techniques to produce miniaturized components in micro-electro mechanical system (MEMS) applications due to its inherent advantages. This work investigates the wear phenomena and the morphology of the copper electrodes during the micro-die sinking process. A numerical model of a single spark is developed assuming the Gaussian distribution of heat flux to estimate the crater dimensions formed in the copper tool electrode (tool wear) used as a result of electric discharge. The crater dimension attained from the ABAQUS finite element model is validated with experimental results using a single spark test setup. Moreover, the effect of input parameters namely capacitance and voltage on the electrode wear rate and surface roughness is also studied. The crater dimensions from the single discharge study are used to formulate the wear model for different possibilities of crater distribution, such as non-overlapping craters, craters with less than 30 % overlap, and 50 % overlap. The electrode wear rate (EWR) also displayed a decline from 20.4 % to 11.6 % and further to 8 % when the overlap was permitted up to 30 % and up to 50 % for the wear model respectively. The developed model results are further compared with experimental results in terms of the electrode wear rate and depth of erosion and the deviations are found to be 20.33 % and 20.55 % respectively

微型放电加工（µ-EDM）工艺因其固有的优势，成为微型机电系统（MEMS）应用中生产微型元件最广泛使用的技术之一。这项工作研究了微模沉积过程中铜电极的磨损现象和形态。假设热通量呈高斯分布，建立了一个单火花数值模型，以估算放电在铜工具电极上形成的凹坑尺寸（工具磨损）。ABAQUS 有限元模型得出的凹坑尺寸与使用单火花测试装置的实验结果进行了验证。此外，还研究了输入参数（电容和电压）对电极磨损率和表面粗糙度的影响。单次放电研究得出的陨石坑尺寸被用于制定不同陨石坑分布可能性的磨损模型，如无重叠陨石坑、重叠率小于 30% 的陨石坑和重叠率为 50% 的陨石坑。当磨损模型允许的重叠率分别达到 30% 和 50%时，电极磨损率 (EWR) 也分别从 20.4% 下降到 11.6%和 8%。就电极磨损率和侵蚀深度而言，所开发模型的结果与实验结果进行了进一步比较，发现偏差分别为 20.33 % 和 20.55 %。

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引用次数: 0

A real-time dual NURBS interpolator with optimised control of flexible acceleration and deceleration for five-axis CNC machining 用于五轴数控加工的实时双 NURBS 插补器，可对灵活的加速和减速进行优化控制

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-10-03 DOI: 10.1016/j.cirpj.2024.09.015

Fei Lou , Hengbo Li , Zhebin Shen , Haorong Zhang , Peng Zhang , Yijie Wu

The limited computing capacity makes it difficult to plan a suitable feedrate profile in real-time for high speed and high accuracy machining of five-axis parametric toolpaths. In this paper, a real-time interpolation algorithm with optimised control of flexible acceleration and deceleration (acc-dec) for the dual NURBS toolpath is proposed. The toolpath is marked as subsegments with similar geometric properties by introducing the five-axis curvature. Machine kinematic and toolpath geometry constraints are considered in the kinematic parameter constraint model. Initial feedrate profiles are solved in a dynamic 3D window which preserves the motion performance of machine tools to a great extent. Convolution is used to smooth the initial feedrate profile to achieve a higher order continuity over the global range. Feedrate fluctuations caused by imprecise parameter interpolation are eliminated through modifying each interpolation periods. Resampling adjusts the position of interpolation points and unify the interpolation periods. All operations mentioned are in series and real-time is strictly guaranteed. Effectiveness of the developed algorithm is validated in simulations and also experimentally on a Self-developed-NC controlled 5-axis machine tool.

由于计算能力有限，很难为五轴参数化刀具路径的高速、高精度加工实时规划合适的进给速度曲线。本文提出了一种实时插补算法，对双 NURBS 刀具路径的柔性加减速（acc-dec）进行了优化控制。通过引入五轴曲率，将刀具路径标记为具有相似几何特性的子段。在运动参数约束模型中考虑了机床运动学和刀具路径几何约束。初始进给速率曲线在动态三维窗口中求解，这在很大程度上保留了机床的运动性能。卷积法用于平滑初始进给速率曲线，以实现全局范围内的高阶连续性。通过修改每个插值周期，消除因参数插值不精确而导致的进给率波动。重新采样可调整插值点的位置，并统一插值周期。上述所有操作都是串联进行的，严格保证了实时性。所开发算法的有效性已在仿真中得到验证，并在自主开发的数控 5 轴机床上进行了实验。

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引用次数: 0

Tool wear prediction based on SVR optimized by hybrid differential evolution and grey wolf optimization algorithms 基于 SVR 的刀具磨损预测，采用混合差分进化和灰狼优化算法进行优化

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-09-27 DOI: 10.1016/j.cirpj.2024.09.013

Jianing Wang , Huiyong Liu , Xiaoling Qi , Yingda Wang , Wei Ma , Song Zhang

Tool wear prediction is key to ensuring product quality and machining efficiency. However, the prediction results of most models are unstable or inaccurate. To address the issues, a tool wear prediction model, based on support vector regression which was optimized by differential evolution and gray wolf optimization algorithms, was proposed in this paper. The method optimized the parameters of support vector regression model through differential evolution and grey wolf optimization algorithms to make the model more balanced in terms of its global and local search capabilities. First, the vibration and power signals were collected by sensors during the milling processes. Then, the features extraction and features selection were performed on the vibration and power signals. Next, the proposed model was developed and trained. Finally, the tool wear was predicted using the proposed model. The results showed that the proposed model had better performance than other models in terms of prediction accuracy and prediction efficiency, and it was applicable to the condition of multiple cutting parameters with generalizability, which will provide some valuable technical support for machining.

刀具磨损预测是确保产品质量和加工效率的关键。然而，大多数模型的预测结果不稳定或不准确。针对这些问题，本文提出了一种基于支持向量回归的刀具磨损预测模型，该模型通过差分进化和灰狼优化算法进行了优化。该方法通过差分进化和灰狼优化算法对支持向量回归模型的参数进行优化，使模型的全局和局部搜索能力更加均衡。首先，通过传感器采集铣削过程中的振动和功率信号。然后，对振动和功率信号进行特征提取和特征选择。然后，开发并训练所提出的模型。最后，使用提出的模型预测刀具磨损。结果表明，所提出的模型在预测精度和预测效率方面都优于其他模型，并且适用于多种切削参数条件，具有普适性，这将为机械加工提供一些有价值的技术支持。

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引用次数: 0

Investigation of the effects of CO2 pre-cooling on the cooling capacity for cryogenic cooling in machining operations 二氧化碳预冷对机械加工中低温冷却能力影响的研究

IF 4.6 2区工程技术 Q2 ENGINEERING, MANUFACTURING

CIRP Journal of Manufacturing Science and Technology

Pub Date : 2024-09-24 DOI: 10.1016/j.cirpj.2024.09.007

Trixi Meier, Jan Harald Selzam, Andreas Röckelein, Nico Hanenkamp

Liquid carbon dioxide (LCO₂) based cryogenic cooling has shown promising results in terms of wear reduction, productivity increase and energy efficiency when machining high-temperature materials. For process-safe use with low pulsation, CO₂ must be fed in the liquid state to cool the process zone. LCO₂ is typically stored in riser bottles in which gaseous and liquid aggregate state coexist. A preliminary study has already shown that the liquefied state of the CO₂ can be stabilized by pre-cooling. In this paper, the influence of a heat exchanger as a pre-cooling system on the cooling capacity of the CO₂ is investigated and the required energy consumption is compared to unstabilized CO₂, pressure increased CO₂ and compressed air. It has been shown that pre-cooling leads to a more energy-efficient increase in the cooling capacity of the CO₂ compared to pressure increased CO₂.

在加工高温材料时，基于液态二氧化碳（LCO2）的低温冷却在减少磨损、提高生产率和能源效率方面显示出良好的效果。为保证加工安全和低脉动，二氧化碳必须以液态输入，以冷却加工区。液态二氧化碳通常储存在气态和液态共存的立管瓶中。初步研究表明，通过预冷可以稳定二氧化碳的液化状态。本文研究了作为预冷系统的热交换器对二氧化碳冷却能力的影响，并将所需能耗与未稳定的二氧化碳、压力增加的二氧化碳和压缩空气进行了比较。结果表明，与增压二氧化碳相比，预冷系统能更有效地提高二氧化碳的冷却能力。

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引用次数: 0