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Experimental investigation on performance of a PODE/methanol two-stroke engine applying fuel blending and dual direct injection strategies 燃油混合和双直喷策略下聚乙二醇/甲醇二冲程发动机性能试验研究
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2026.129765
Pengbo Dong , Zhuohan Sun , Xiaoying Xu , Changhong Ma , Lu Yan , Qingyang Wang , Liyun Fan , Zhenxian Zhang , Wuqiang Long
As highly promising low-carbon fuel power system, methanol engine in diesel-methanol dual direct injection (DDI) strategy still suffers from poor ignition characteristics under low-load conditions, leading to frequent misfires, low substitution rates, and high emissions. On the other hand, polyoxymethylene dimethyl ethers (PODE) exhibits superior ignition performance and soot reduction capability compared to diesel, while it remains unclear whether it can effectively improve methanol substitution rate under low and medium loads. Furthermore, DDI systems require complex dual injection hardware, which limits practical implementation. Given that PODE and methanol are fully miscible, PODE/methanol blends direct injection mode can simplify the injection system and potentially offer more effective ignition points. However, studies focusing on PODE/methanol DDI and blend fuel strategies remain scarce, and systematic experimental comparisons between them under low and medium loads are also lacking. In this study, performance characteristics of PODE/methanol dual direct injection (P-M DDI) mode were investigated firstly under different methanol injection mass and low/medium loads using a low-speed two-stroke engine. The maximum methanol injection mass was 97.6 mg/cycle when the PODE injection mass was fixed at 39.4 mg/cycle. Then, PODE/methanol blends direct injection (P50-DI) mode was conducted, and performance characteristics were compared between P-M DDI mode and P50-DI mode under different fuel injection timings. The results reveal that in P-M DDI mode, PODE flame ignites methanol rapidly, resulting in combustion phase characteristics with dual-peak heat release. The engine output torque exhibits a proportional increase with the methanol injection mass rising, indicating that the output is effectively regulated through “quantitative regulation” approach. The maximum energy replacement ratio of methanol (ERM) reaches 76% at 50% load. However, a higher ERM results in increased COVIMEP, primarily because the flame propagation is hindered, which elevated the variability in methanol combustion efficiency. Furthermore, delaying the PODE injection timing shortens the combustion duration by 7.5% and improves the indicated thermal efficiency (ITE) by 7.6%. Compared to P50-DI mode, P-M DDI mode shows shorter combustion duration and higher ITE due to that methanol can be ignited rapidly by PODE spray flame and achieve fast combustion. In contrast, the superior premix uniformity and micro-explosion effect of methanol in P50-DI mode contribute to the reduction of NOx and CO emissions. These findings provide practical guidance for optimizing combustion and emission characteristics of methanol-based dual-fuel engines under low and medium load conditions.
甲醇发动机作为一种极具发展前景的低碳燃料动力系统,在柴油-甲醇双直喷(DDI)策略下,仍存在低负荷工况下点火特性不佳、失火频繁、替代率低、排放高的问题。另一方面,聚氧二甲基醚(PODE)的点火性能和减灰能力优于柴油,但在中、低负荷下是否能有效提高甲醇取代率尚不清楚。此外,DDI系统需要复杂的双注入硬件,这限制了实际实施。由于PODE和甲醇是完全可混溶的,因此PODE/甲醇混合直喷模式可以简化喷射系统,并可能提供更有效的着火点。然而,针对PODE/甲醇DDI和混合燃料策略的研究仍然很少,并且在中、低负荷下也缺乏系统的实验比较。本研究首先在低速二冲程发动机上,研究了不同甲醇喷射质量和中低负荷工况下PODE/甲醇双直喷(P-M DDI)模式的性能特征。以39.4 mg/cycle固定PODE的注射质量时,甲醇的最大注射质量为97.6 mg/cycle。然后进行了PODE/甲醇共混直喷(P50-DI)模式,比较了P-M DDI模式和P50-DI模式在不同喷油时间下的性能特性。结果表明,在P-M DDI模式下,PODE火焰快速点燃甲醇,产生双峰放热的燃烧相特征;发动机输出转矩随甲醇喷射质量的增大呈比例增大,表明通过“定量调节”的方式对输出进行了有效调节。在50%负荷下,甲醇的最大能量替代率(ERM)达到76%。然而,较高的ERM会导致COVIMEP增加,这主要是因为火焰传播受到阻碍,从而增加了甲醇燃烧效率的可变性。此外,延迟PODE喷射时间可将燃烧时间缩短7.5%,并将指示热效率(ITE)提高7.6%。与P50-DI模式相比,P-M DDI模式燃烧持续时间更短,ITE更高,这是由于甲醇可以被PODE喷射火焰快速点燃,实现快速燃烧。相比之下,甲醇在P50-DI模式下优异的预混均匀性和微爆炸效果有助于减少NOx和CO的排放。这些研究结果为优化低、中负荷条件下甲醇基双燃料发动机的燃烧和排放特性提供了实践指导。
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引用次数: 0
Pilot test and numerical research of a novel non-heat exchange temperature control technology for CAES underground caverns CAES地下洞室新型非换热温控技术的中试与数值研究
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2026.129776
Junhui Liao , Zhongming Jiang , Xi Lu , Gaofeng Ma , Zhaofeng Shi , Chenzhi Liu , Yang Ji , Jiahao Li , Xiangyi Huang , Zhezhen Xiao , Xue Yang
Temperature control is crucial for the safe operation of compressed air energy storage (CAES) underground caverns. While the heat exchange technology has been widely proved, research on low-cost non-heat exchange temperature control (NETC) technology—relying on active airflow restructuring rather than external thermal intervention to reduce the local high temperature in the cavern—remains largely theoretical. To validate the efficacy of NETC technology, a pilot-scale test was conducted in a tunnel-type cavern, complemented by numerical simulations for synergistic validation and mechanism exploration. Experimental results demonstrate that with NETC, the average temperature rise of each tunnel and monitored point was remarkably consistent at 11.7 ± 0.3 °C during air charging. The temperatures at the same elevation (waist of the cavern) of the typical section were uniform but noticeably higher than those at the bottom. The maximum temperature difference within the same measured section reached 5.5 °C, revealing a non-uniform temperature distribution of the vertical section. Numerical simulations show that NETC measures reduce the maximum temperature by 17.2% and decrease the high-temperature zone volume by 23%. The mechanism of NETC measures is to actively intervene in the air flow field, promote the turbulence formation, and enhance the convection heat exchange of air. In engineering-scale applications, NETC technology could reduce the temperature gradient, enhance the structural stability, and lower the construction costs, offering a technically and economically feasible solution for the temperature control issue of CAES underground caverns.
温度控制是压缩空气储能地下洞室安全运行的关键。虽然换热技术已经得到了广泛的验证,但依靠主动气流重组而非外部热干预来降低洞室局部高温的低成本非换热温度控制(NETC)技术的研究在很大程度上仍停留在理论阶段。为了验证NETC技术的有效性,在隧道型洞室进行了中试试验,并辅以数值模拟进行了协同验证和机理探索。实验结果表明,在NETC条件下,进气过程中各隧道和监测点的平均温升均为11.7±0.3℃,具有显著的一致性。典型断面在相同高度(洞穴腰部)的温度是均匀的,但明显高于底部。同一测量截面内最大温差达到5.5℃,显示出垂直截面温度分布不均匀。数值模拟表明,NETC措施使最高温度降低了17.2%,使高温区体积减小了23%。NETC措施的机制是积极干预空气流场,促进湍流的形成,增强空气对流换热。在工程规模应用中,NETC技术可以减小温度梯度,提高结构稳定性,降低施工成本,为CAES地下洞室的温度控制问题提供了技术上和经济上可行的解决方案。
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引用次数: 0
Energy consumption optimization of thermal management system for extended-range electric vehicles based on 11-way valve heat pump architecture 基于11通阀热泵架构的增程式电动汽车热管理系统能耗优化
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2025.129529
Liange He, Jinwang Tang, Limin Wu, Yan Zhang, Haijun Mo
The thermal management of extended-range electric vehicles (EREV) presents a unique challenge due to the dynamic interplay between the intermittent, high-grade heat from the range extender and the continuous, low-grade heat from the electric drive. To address this, this paper proposes a novel integrated thermal management system (ITMS) featuring a heat pump and a purpose-designed 11-way valve topology. This architecture enables unique hybrid heating modes for maximum energy efficiency. Furthermore, an EREV state-aware control strategy is developed to coordinate the different heat sources, ensuring seamless thermal management during transitions between charge-depleting and charge-sustaining modes. Simulation results, validated by experimental data, demonstrate robust performance across diverse conditions. Under −7 °C, the proposed system reduces energy consumption by 4.59% ± 0.21% in the CLTC and 4.52% ± 0.23% in the more dynamic WLTC, proving its adaptability to different driving behaviors. Additionally, a parametric study reveals an “inverted-U" efficiency trend across the −20 °C to 0 °C range, with peak savings reaching 5.20% ± 0.24%. Detailed contribution analysis further quantifies that while the heat pump is the primary saver, the 11-way valve integration itself contributes a distinct 7.6% (CLTC) and 7.3% (WLTC) of the total savings, validating the effectiveness of the advanced architecture.
增程式电动汽车(EREV)的热管理面临着独特的挑战,因为增程式增压器产生的间歇性高级热量与电力驱动产生的连续低级热量之间存在动态相互作用。为了解决这个问题,本文提出了一种新的集成热管理系统(ITMS),该系统具有热泵和专门设计的11通阀拓扑结构。这种结构可以实现独特的混合加热模式,以实现最大的能源效率。此外,开发了一种EREV状态感知控制策略来协调不同的热源,确保在电荷耗尽和电荷保持模式之间转换时无缝的热管理。仿真结果经实验数据验证,在不同条件下均具有良好的性能。在- 7°C下,该系统在CLTC和WLTC下分别降低了4.59%±0.21%和4.52%±0.23%的能耗,证明了其对不同驾驶行为的适应性。此外,参数研究显示,在−20°C至0°C范围内,效率呈“倒u”型趋势,峰值节能达到5.20%±0.24%。详细的贡献分析进一步量化,虽然热泵是主要的节省,但11通阀集成本身贡献了7.6% (CLTC)和7.3% (WLTC)的总节省,验证了先进架构的有效性。
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引用次数: 0
Development and performance evaluation of MPCM slurry for battery thermal management via immersion cooling 浸没冷却电池热管理用MPCM浆料的研制及性能评价
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2026.129779
Zhihui Zhang , Rongfang Qiu , Zhenlang Mai , Tingting Wu , Changhong Wang , Zhixuan Liang
Immersion cooling offers a promising solution to the thermal safety challenges of high-energy-density energy storage systems. However, its broader adoption has been limited by the inherently low heat transfer efficiency of conventional single-phase immersion coolants. To address this fundamental constraint, this study developed a novel microencapsulated phase change material (MPCM) and its corresponding slurry (MPCMS), specifically engineered to concurrently enhance the thermal conductivity and specific heat capacity of the coolant. A comprehensive experimental characterization of the synthesised materials was conducted, followed by their innovative deployment in an immersion-cooled battery thermal management system (BTMS). The thermal management performance was rigorously evaluated through numerical simulation, systematically revealing the advantages of this novel coolant. The results show that the SiC-modified MPCM (MPCM-SiC) achieves a thermal conductivity of 0.247 W/m·K, a 37.2% improvement over its unmodified counterpart, while retaining a high encapsulation efficiency of 77.96% and excellent thermal cycling stability. The derived MPCMS-SiC slurry exhibits corresponding increases in thermal conductivity and specific heat capacity of up to 18.39% and 325.29%, respectively, confirming its superior heat transfer and energy storage capabilities. In a BTMS evaluation, the 10 wt% MPCMS-SiC formulation reduced the maximum battery pack temperature and the maximum temperature differential to 38.12 °C and 5.34 °C. These values represent reductions of 9.28% and 23.28% compared to mineral oil, demonstrating simultaneous optimization of temperature suppression and uniformity. Furthermore, this approach reduced the system pumping power by 88.69%, significantly improving overall energy efficiency.
浸入式冷却为高能量密度储能系统的热安全挑战提供了一个有前途的解决方案。然而,由于传统的单相浸入式冷却剂固有的低传热效率,其广泛采用受到限制。为了解决这一基本限制,本研究开发了一种新型微封装相变材料(MPCM)及其相应的浆液(MPCMS),专门设计用于同时提高冷却剂的导热性和比热容。对合成材料进行了全面的实验表征,随后将其创新性地应用于浸入式冷却电池热管理系统(BTMS)中。通过数值模拟对其热管理性能进行了严格的评估,系统地揭示了这种新型冷却剂的优势。结果表明,sic改性的MPCM (MPCM- sic)的导热系数为0.247 W/m·K,比未改性的MPCM提高了37.2%,同时保持了77.96%的封装效率和良好的热循环稳定性。制备的MPCMS-SiC料浆导热系数和比热容分别提高了18.39%和325.29%,证明了其优越的传热和储能能力。在BTMS评估中,10%的MPCMS-SiC配方将电池组的最大温度和最大温差降低到38.12°C和5.34°C。这些值分别比矿物油降低了9.28%和23.28%,表明温度抑制和均匀性同时优化。此外,该方法将系统泵送功率降低了88.69%,显著提高了整体能源效率。
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引用次数: 0
Multi-objective quantum differential evolution with Kolmogorov–Arnold network surrogate modeling for plate-fin heat exchanger design 基于Kolmogorov-Arnold网络代理模型的板翅式换热器设计多目标量子差分演化
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2025.129553
Viviana Cocco Mariani , Carlos Augusto Richter do Nascimento , Leandro dos Santos Coelho
This study presents a data-driven framework for the multi-objective thermodynamic optimization of counter-flow plate-fin heat exchangers (PFHEs), addressing the complex trade-offs between thermal performance, pressure drop, and technical viability. The proposed methodology integrates a novel Multiobjective Quantum-inspired Self-adaptive Differential Evolution (MOQSDE) algorithm with a surrogate model based on a Kolmogorov–Arnold Network (KAN) and its symbolic approximation. The KAN model is trained using data from computational fluid dynamics simulations, effectively approximating the nonlinear behavior of the PFHE and reducing the computational cost associated with traditional iterative design methods. The framework optimizes fin geometry and plate spacing parameters to simultaneously maximize heat transfer efficiency while minimizing pressure drop and total annualized cost. The KAN surrogate, trained on a large dataset of computational fluid dynamics (CFD) simulations, achieved outstanding predictive performance with coefficients of determination (R2) exceeding 0.996 for pressure drop and above 0.96 for heat transfer coefficients, ensuring accuracy and generalization. The MOQSDE algorithm, enhanced by quantum-inspired operators, entropy-driven parameter adaptation, and dual-space diversity metrics, demonstrated superior convergence and diversity compared to benchmark optimizers, yielding statistically significant improvements in hypervolume and entropy measures. The combined KAN–MOQSDE framework identified PFHE designs that reduced volume and pressure drop by more than 12% while increasing thermal effectiveness relative to baseline configurations. These results confirm that the proposed approach provides both computational efficiency and physical interpretability, offering a robust pathway for the systematic design of compact heat exchangers.
本研究提出了一个数据驱动的框架,用于逆流板翅式换热器(PFHEs)的多目标热力学优化,解决了热性能、压降和技术可行性之间的复杂权衡。该方法将一种新的多目标量子启发自适应差分进化(MOQSDE)算法与基于Kolmogorov-Arnold网络(KAN)及其符号逼近的代理模型相结合。KAN模型使用计算流体动力学模拟数据进行训练,有效地逼近了PFHE的非线性行为,降低了传统迭代设计方法的计算成本。该框架优化了翅片几何形状和板间距参数,以最大限度地提高传热效率,同时最小化压力降和年化总成本。KAN代理在大型计算流体动力学(CFD)模拟数据集上进行了训练,获得了出色的预测性能,压降的决定系数(R2)超过0.996,传热系数超过0.96,确保了准确性和泛化性。与基准优化器相比,MOQSDE算法在量子启发算子、熵驱动参数自适应和双空间多样性指标的增强下,表现出了卓越的收敛性和多样性,在超大容量和熵度量方面产生了统计学上显著的改进。结合KAN-MOQSDE框架,PFHE设计可以将体积和压降降低12%以上,同时相对于基线配置提高热效率。这些结果证实了所提出的方法具有计算效率和物理可解释性,为紧凑型换热器的系统设计提供了强有力的途径。
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引用次数: 0
A two-stage ventilation strategy for thermal safety and energy efficiency in extreme tunnel conditions 极端隧道条件下热安全和能源效率的两阶段通风策略
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-10 DOI: 10.1016/j.applthermaleng.2026.129734
Zhaoxing Li, Guohui Feng, Jialin Sun, Kailiang Huang, Yipeng Liu, Yang Liu, Jiaxing Wei, Xiru Wang
Effective ventilation is essential for ensuring thermal safety and improving energy efficiency in tunnels constructed under high-temperature and high-humidity conditions. Conventional ventilation systems with fixed operating parameters often fail to provide adequate thermal control in such extreme environments. To address this limitation, a two-stage combined ventilation strategy is proposed based on a validated rock-air bidirectional heat-moisture coupling numerical model. The ventilation process is divided into two sequential stages according to construction characteristics. The first stage applies short-term, high-intensity ventilation immediately after blasting to rapidly remove heat and dust in the absence of personnel, while the second stage provides sustained cooling during construction with the airflow velocity restricted to no more than 6 m/s to ensure operational safety. A total of twenty-seven two-stage ventilation schemes were systematically evaluated by combining supply-air flow rates ranging from 35 to 55 m3/s with supply-air temperatures between 15 °C and 25 °C, and compared with a conventional single-stage strategy. Cooling performance and energy consumption were assessed using air temperature, heat index, and wet-bulb globe temperature as thermal safety indicators. The results show that the optimal two-stage scheme achieves energy savings of 76.45%, 77.69%, and 31.82% when evaluated using air temperature, heat index, and wet-bulb globe temperature, respectively, compared with the conventional strategy.
在高温高湿条件下施工的隧道,有效的通风是保证热安全和提高能源效率的关键。在这种极端环境下,具有固定运行参数的传统通风系统往往无法提供足够的热控制。针对这一局限性,提出了一种基于岩石-空气双向热湿耦合数值模型的两级联合通风策略。通风过程根据施工特点分为两个顺序阶段。第一阶段在爆破后立即进行短期、高强度的通风,在没有人员的情况下迅速散热和除尘;第二阶段在施工过程中进行持续冷却,风速限制在不超过6m /s,以确保作业安全。通过将送风流量从35至55 m3/s,送风温度在15°C至25°C之间结合起来,系统评估了27种两级通风方案,并与传统的单级通风策略进行了比较。采用空气温度、热指数和湿球温度作为热安全指标来评估冷却性能和能耗。结果表明,采用空气温度、热指数和湿球温度评价时,两阶段优化方案与常规方案相比节能效果分别为76.45%、77.69%和31.82%。
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引用次数: 0
Modeling of oscillating heat pipes: Equilibria, stagnation, startup, bifurcation, oscillation, conductance, and statistics 振荡热管的建模:平衡,停滞,启动,分岔,振荡,电导和统计
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-09 DOI: 10.1016/j.applthermaleng.2026.129761
Carmen Chicone , Z.C. Feng , Stephen J. Lombardo
A reduced-order model has been developed to describe the nonlinear dynamics of oscillating heat pipes (OHPs). Its formulation consists of two first-order ordinary differential equations for momentum balance and one for the net rate of evaporation and condensation, yielding three equations per liquid-slug/vapor-plug pair. The model captures key aspects of OHP behavior, including equilibrium, stagnation, startup, bifurcation, oscillation, and thermal conductance. With fixed system parameters, the model’s dynamics depend in a complex manner on initial conditions, necessitating statistical averaging to determine thermal conductance. The model’s relative simplicity reduces computational overhead, permitting hundreds to thousands of simulation runs on a supercomputer to compute averages with 95% Z-confidence intervals, allowing statistically meaningful conclusions. The dependence of total thermal conductance — incorporating both latent and sensible heat effects — on temperature difference, number of slug-plug pairs, fill fraction, and number of turns is examined. Using the framework of nonlinear dynamics, we explain bifurcation phenomena, stopovers, multiple attractors, and transitions among attractors. These statistical analyses of large-scale simulations provide a new basis for the design and optimization of OHP performance.
建立了一个描述振荡热管非线性动力学的降阶模型。其公式由动量平衡的两个一阶常微分方程和蒸发和冷凝净速率的一个一阶常微分方程组成,每个液塞/气塞对产生三个方程。该模型捕获了OHP行为的关键方面,包括平衡、停滞、启动、分岔、振荡和热导。在系统参数固定的情况下,模型的动力学以复杂的方式依赖于初始条件,需要统计平均来确定热导率。该模型的相对简单性降低了计算开销,允许在超级计算机上运行数百到数千次模拟,以95%的z置信区间计算平均值,从而得出具有统计意义的结论。总导热系数(包括潜热和显热效应)对温差、段塞对数、填充分数和匝数的依赖性进行了检验。利用非线性动力学的框架,我们解释了分岔现象、中途停留、多吸引子和吸引子之间的转换。这些大规模仿真的统计分析为OHP性能的设计和优化提供了新的依据。
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引用次数: 0
CFD and experimental study of cyclone heat exchanger performance: NTU-effectiveness analysis 旋风换热器性能的CFD与实验研究:ntu -有效性分析
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-09 DOI: 10.1016/j.applthermaleng.2025.129590
V. Velukumar , S.D. Sekar , T. Mothilal
A novel cyclone heat exchanger (CHX) was designed for heat exchange between gas-solid in the mixture and evaluated for its applicability in the industrial drying of granular materials. This research investigates the influence of air flow rate (300–1500 m/min), solid particulate loading rate (30–150 g/min), and particulate size (300–500 μm) on the number of transfer units (NTU) and thermal effectiveness (ε). Computational Fluid Dynamics (CFD) simulations were carried out using the Reynolds Stress Turbulence Model (RSTM) and Discrete Phase Model (DPM) and validated with laboratory-scale experiments. The findings indicated that an increasing air flow rate improved NTU (1.10–2.37) and ε (0.56–0.88) due to higher outlet temperatures and longer particle residence time. Conversely, larger particles and elevated feed rates decreased effectiveness by 13 to 17.5% due to reduced residence time and a smaller heat transfer area. A new correlation for thermal effectiveness was introduced utilizing non-dimensional variables: holdup mass ratio (ᴨ1), mass flow rate ratio (ᴨ2), and particle-to-cyclone diameter ratio (ᴨ3). The correlation proves strong relation with CFD (R2 = 0.9992) and experimental results (R2 = 0.9257), offering a reliable tool for CHX design and performance prediction.
设计了一种新型的旋风换热器(CHX),用于混合物中的气固交换,并对其在颗粒物料工业干燥中的适用性进行了评价。研究了空气流速(300-1500 m/min)、固体颗粒加载速率(30-150 g/min)和颗粒尺寸(300-500 μm)对传热单元数(NTU)和热效率(ε)的影响。采用雷诺应力湍流模型(RSTM)和离散相模型(DPM)进行了计算流体动力学(CFD)模拟,并通过实验室规模的实验进行了验证。结果表明:随着空气流量的增加,NTU值(1.10 ~ 2.37)和ε值(0.56 ~ 0.88)均因出口温度的升高和颗粒停留时间的延长而提高。相反,较大的颗粒和较高的进料速率会降低13 - 17.5%的效率,因为停留时间缩短和传热面积减小。利用无量纲变量引入了热效率的新相关性:含率质量比(ᴨ1),质量流率比(ᴨ2)和颗粒与旋风直径比(ᴨ3)。相关系数与CFD (R2 = 0.9992)和实验结果(R2 = 0.9257)具有较强的相关性,为CHX设计和性能预测提供了可靠的工具。
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引用次数: 0
Combustion mode vs. misfire: Evidence of relative fuel injection timing of ammonia-diesel dual-fuel engine 燃烧模式与失火:证据相对燃油喷射时间的氨柴油双燃料发动机
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-09 DOI: 10.1016/j.applthermaleng.2026.129768
Yuelong Li , Huibing Gan , Long Wang , Zonghan Li , Daoyi Lu , Ankang Guo , Huaiyu Wang
High ammonia energy fraction (AEF) dual-fuel engines represent a promising pathway for significant carbon emission reduction. Nevertheless, the liquid ammonia direct-injection mode presents challenges in maintaining combustion stability at high AEF. This study investigates the influence of relative injection timing on combustion modes and misfire intervals, thereby clarifying the combustion instability mechanism in ammonia-diesel dual-fuel engines with high ammonia substitution rates. The results show that injecting liquid ammonia 9.5 °CA earlier than diesel fuel, compared to the ammonia premixed mode, increases the indicated thermal efficiency by 4%, and reduces NOX and unburned ammonia emissions by 22% and 86%, respectively. Moreover, the spatiotemporal overlap between the liquid ammonia and diesel fuel injection zones is identified as the primary cause of misfire. Misfire occurs within a window of liquid ammonia injection timings from −5.25 °CA to 0.1 °CA. Increasing the distance between the liquid ammonia and diesel injectors can shorten this misfire phase. Furthermore, under identical operating conditions, the diffusion combustion mode demonstrates poorer combustion stability. The critical temperature for misfires is largely insensitive to variations in diesel injection timing and the distance between the injectors. This critical temperature clusters around 850 K in the premixed combustion mode and around 930 K in the diffusion combustion mode. The cause of the temperature difference is related to the locally high equivalent ratio in the diffusion mode. This research provides valuable insights for preventing misfire and enhancing combustion stability.
高氨能分数(AEF)双燃料发动机为显著减少碳排放提供了一条有前景的途径。然而,液氨直喷模式在保持高AEF下的燃烧稳定性方面存在挑战。本研究考察了相对喷油时间对燃烧模式和失火间隔的影响,从而阐明了高氨取代率氨柴油双燃料发动机的燃烧不稳定机理。结果表明,与氨预混合模式相比,早于柴油喷射9.5°CA的液氨,指示热效率提高4%,NOX和未燃氨排放量分别降低22%和86%。此外,液氨和柴油喷射区之间的时空重叠被确定为失火的主要原因。在- 5.25°CA至0.1°CA的液氨注入时间窗口内发生失火。增加液氨和柴油喷油器之间的距离可以缩短这一失火阶段。在相同工况下,扩散燃烧方式的燃烧稳定性较差。失火的临界温度在很大程度上对柴油喷射时间和喷油器之间距离的变化不敏感。该临界温度在预混合燃烧模式下约为850 K,在扩散燃烧模式下约为930 K。产生温差的原因与扩散模式下局部较高的等效比有关。该研究为防止失火和提高燃烧稳定性提供了有价值的见解。
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引用次数: 0
Recent advances in machine learning for advanced building envelopes: From prediction to optimisation 先进建筑围护结构机器学习的最新进展:从预测到优化
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2026-01-09 DOI: 10.1016/j.applthermaleng.2026.129747
Xueren Li , Liwei Zhang , Yin Tang , Qingyi Chen , Weijie Sun , Xiang Fang , Yao Tao , Bichen Shang , Jiyuan Tu
Innovations in building envelopes are a main pathway toward zero-carbon buildings. However, the integration of renewable energy systems and novel materials increases multi-scale and multi-physics coupling, which complicates prediction and intelligent management. Integrating Artificial Intelligence (AI) into advanced envelope design is increasingly necessary and trending. This paper provides a holistic review of recent research on integrating machine learning (ML) with advanced building envelope designs that require considerations of cross-scale environmental and physical parameters. Popular ML algorithms, data input requirements, and output generation are elucidated, aiming to shed light on the selection of appropriate algorithms for specific datasets. ML-involved studies related to specific building envelope types (e.g., building-integrated photovoltaic (BIPV), PCM-integrated walls, advanced glazing systems, green roofs, etc.) are discussed. The review highlights the capabilities of emerging AI technologies in predicting renewable-energy related design parameters (e.g., material properties and environmental impacts) that contribute to optimisation and smart management. In particular, given the dependence of renewable energy on outdoor environment, this paper focuses on the influence of macro-scope urban scale environment to achieve environment-buildings integration from an AI perspective. This work is anticipated to yield valuable insights in promoting the AI-driven building envelope design solutions to tackle the emerging challenges in integrating renewable energy and evaluating from a macro-scope view.
建筑围护结构的创新是实现零碳建筑的主要途径。然而,可再生能源系统和新材料的集成增加了多尺度和多物理场的耦合,这使得预测和智能管理变得复杂。将人工智能(AI)集成到先进的信封设计中是越来越必要和趋势。本文全面回顾了最近将机器学习(ML)与需要考虑跨尺度环境和物理参数的先进建筑围护结构设计相结合的研究。阐述了流行的ML算法、数据输入要求和输出生成,旨在阐明针对特定数据集选择适当算法的方法。ml涉及的研究与特定的建筑围护结构类型(例如,建筑集成光伏(BIPV), pcm集成墙,先进的玻璃系统,绿色屋顶等)进行了讨论。该综述强调了新兴人工智能技术在预测可再生能源相关设计参数(例如材料特性和环境影响)方面的能力,这些参数有助于优化和智能管理。特别是考虑到可再生能源对室外环境的依赖,本文从人工智能的角度出发,关注宏观城市尺度环境的影响,实现环境与建筑的融合。这项工作有望在促进人工智能驱动的建筑围护结构设计解决方案方面产生有价值的见解,以应对整合可再生能源和从宏观角度进行评估的新挑战。
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Applied Thermal Engineering
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