皮带输煤暗道通风排尘改造方案优化研究

为了解决皮带输煤暗道运输过程中粉尘污染严重及冬季供暖不足问题,对暗道通风供热系统进行了优化改造研究。以中煤平朔安家岭264输煤暗道为例,基于气固两相流理论,利用CFD模拟方法,对暗道内由风速对悬浮粉尘浓度分布的影响规律进行数值仿真。模拟结果显示:当输煤暗道排尘风速由0.25 m/s升至0.35 m/s时,粉尘浓度降为3.2 mg/m3,暗道最大通风阻力为245.94 Pa,最低换热量747.68 kW。基于数值模拟结果,从3种优化方案中选定一压一抽联合式通风除尘方案进行改造,现场实测除尘效果良好,表明所提出的输煤暗道通风除尘方案具有实践指导意义。     

大气土壤耦合的埋地燃气管道泄漏扩散数值分析

为了研究埋地燃气管道泄漏燃气在非稳态泄漏条件下的扩散行为,基于燃气管道非稳态泄漏大孔模型,应用CFD分别求解土壤和大气扩散方程,通过丙烷地面扩散通量耦合了土壤和大气环境,进行了泄漏扩散的数值模拟,所得模拟计算结果与地上泄漏扩散数值模拟结果进行了对比分析。研究结果表明:耦合模拟条件下,风速仍是影响丙烷扩散距离和高度的主要因素;温度和相对湿度对丙烷扩散有相对较小的影响;与埋地泄漏相比,不同条件下地上泄漏的扩散距离和扩散高度均有误差,水平扩散距离误差普遍较大,扩散高度个别情况下误差较大;地上泄漏条件下的模拟结果数值偏大,对事故的预测和评估准确性会产生显著影响。     

人工煤气管道萘颗粒沉积规律研究

针对萘在人工煤气管道中沉积会造成管道堵塞,影响管道的安全运行的这一问题,以昆明人工煤气管道为例,运用计算流体动力学软件Fluent,选用离散相模型和雷诺应力模型,对水平直管、水平弯管和三通管进行萘颗粒沉积的数值模拟,对于不同的管径、弯曲比、管径比,分别分析萘颗粒直径、入口速度、温度及压力对萘颗粒沉积的影响。研究结果表明:水平直管、水平弯管、三通管中的萘颗粒沉积率与颗粒粒径成正相关关系,而与气流入口速度、压力成负相关关系;萘颗粒在人工煤气管道中的沉积率主要受颗粒直径、气流入口速度的影响;萘颗粒的沉积率随着水平直管的管径增大而增大,随着水平弯管的弯曲比增大而增大,随着三通管的管径比增大而先增大后减小;可通过适当增大管内煤气输送速度、压力,降低温度来降低萘颗粒在人工煤气管道中的沉积速度,进而减少萘颗粒沉积的发生。     

台兰河流域地下水系统数值模拟

地下水数值模拟是地下水在多孔介质中分布过程机理的模拟,以流域水量均衡为基础,应用ArcView GIS与FEFLOW专业地下水模拟软件,根据研究区水文地质勘探资料、抽水试验及地下水水位长期观测资料,建立了内陆河流域二维地下水运动模拟模型。采用Kringing、Aki-ma插值方法和Galerkin有限元三角形网格剖分技术,求解模型,模拟了台兰河流域地下水运动特征。从模拟结果可以看出,所建立的水文地质概念模型和数学模型是正确的,选取的水文地质参数和计算的源汇项基本合理,模拟结果与实测数值比较吻合,符合台兰河流域地下水的实际情况,能够进行该区域地下水的动态预报,可为研究区水资源的合理开发提供科学依据和技术指导。     

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias < 2% and assisting in air quality policy making in near real time.     

Numerical modeling and optimization of a power augmented S-type vertical axis wind turbine

An axial symmetry augmented vertical axis wind turbine, which is suitable for arbitrary wind directions, is proposed in this paper. In order to improve the power generation ability of the S-type vertical axis wind turbine, a set of so-called “collection-shield boards” are installed symmetrically around the rotating S-type rotor. The flow fields around this type of wind turbine are numerically simulated with the aid of CFD method. The optimized design of geometrical parameters of the rotor and collection-shield boards is conducted by using the orthogonal design method. The obtained results suggest that the power output of the optimized augmented wind turbine can reach nearly three times higher than that of the conventional S-type vertical axis wind turbine.     

The convective hot air drying of Lactuca sativa slices

The storage of fresh agricultural products is not easy because of its high moisture. Dehydration is an efficient preservation method. The investigation of drying modeling and transfer characteristics are important for selecting operating conditions and equipment design. The drying behavior of Lactuca sativa slices, with the thickness of 2 mm, was investigated at 60.0–80.0°C and 0.60–1.04 m sec^?1 velocity in a convective hot air drier. The mass transfer during the drying process was described using six thin drying models. The convective heat transfer coefficient α and mass transfer coefficient k_H were finally calculated. The results showed that the drying process could be separated into three stages including accelerating rate, constant rate, and falling rate period, which was influenced by hot air temperature and velocity, and the Modi?ed Page model agreed well with the experimental data. When the operating temperature was increased from 60.0°C to 80.0°C, α was found increased from 88.07 to 107.93 W·m^?2·K^?1, and k_H increased from 46.32 × 10^–3 to 68.04 × 10^–3 kg·m^?2·sec^?1·ΔH^?1. With the increase of air velocity from 0.60 to 1.04 m·sec^?1, α was increased from 78.85 to 101.35 W·m^?2·K^?1, and k_H was enhanced from 51.78 × 10^–3 to 65.85 × 10^–3 kg·m^?2·sec^?1·ΔH^?1.     

Evaluation of Gauge‐Radar Merging Methods Using a Semi‐Distributed Hydrological Model in the Upper Thames River Basin,Canada

Gauge‐radar merging methods combine rainfall estimates from rain gauges and radar to capitalize on the strengths of the individual instruments. The performance of four well‐known gauge‐radar merging methods, including mean field bias correction, Brandes spatial adjustment, local bias correction using kriging, and conditional merging, are examined using Environment Canada radar and the Upper Thames River Basin in southwestern Ontario, Canada, as a case study. The analysis assesses the effect of gauge‐radar merging methods on: (1) the accuracy of predicted rainfall accumulations; and (2) the accuracy of predicted streamflows using a semi‐distributed hydrological model. In addition, several influencing factors (i.e., gauge density, storm type, basin type, proximity to the radar tower, and time‐step of adjustment) are analyzed to determine their effect on the performance of the rainfall estimation techniques. Confirming results of previous studies, the merging methods provide an increase in the accuracy of both rainfall accumulation estimations and predicted streamflows. The results also indicate specific factors such as gauge density, rainfall intensity, and time‐step of adjustment can reduce the accuracy of merging methods and play a key role in the examination of its use for operational purposes. Results provide guidance for hydrologists and engineers assessing how best to apply corrected radar products to improve rainfall estimation and hydrological modeling accuracy.     

Climate Change Impacts on Local Flood Risks in the U.S. Northeast: A Case Study on the Connecticut and Merrimack River Basins

This study investigates the potential impacts of climate change on future flows in the main stem of the Connecticut and Merrimack rivers within Massachusetts. The study applies two common climate projections based on (Representative Concentration Pathways), RCP 4.5 and RCP 8.5 and downscaled gridded climate projections from 14 global climate models (GCMs) to estimate the 100‐year, 24‐h extreme precipitation events for two future time‐periods: near‐term (2021–2060) and far‐term (2060–2099). 100‐year 24‐h precipitation events at near‐ and far‐term are compared to GCM‐driven historical extreme precipitation events during a base period (1960–1999) and results for RCP 8.5 scenario show average increases between 25%–50% during the near‐term compared to the base period and increases of over 50% during the far‐term. Streamflow conditions are generated with a distributed hydrological model where downscaled climate projections are used as inputs. For the near‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest 2.9%–8.1% increases in the 100‐year, 24‐h flow event in the Connecticut and an increase of 9.9%–13.7% in the Merrimack River. For the far‐term, the medians of the GCMs using the RCP 4.5 and RCP 8.5 suggest a 9.0%–14.1% increase in the Connecticut and 15.8%–20.6% for the Merrimack River. Ultimately, the results presented here can be used as a guidance for the long‐term management of infrastructures on the Connecticut and Merrimack River floodplains.     

Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature

This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.