Energy retrofit and conservation of a historic building using multi-objective optimization and an analytic hierarchy process

When deciding on the best historic building retrofit,energy savings and thermal comfort can be quantitatively evaluated using an energy model,whereas conservation compatibility is intrinsically qualitative and reflects the perspective of the local heritage authority. We present a methodology that permits finding and comparing optimal retrofits for historic buildings in a multi-perspective and quantitative way. We use an analytic hierarchyprocess to quantify conservation compatibility by distilling a conservation score from the opinions of 10 experts in the field. This score,along with energy needs for heating and cooling and thermal comfort,are the three targets of a multi-objective optimization aimed at identifying optimal retrofits for a medieval building in the north of Italy,destined to become a museum. Retrofit measures considered were different kinds of external and internal envelope insulation,improvement of airtightness,replacement of windows,and ventilative cooling. The result is a portfolio of optimal retrofits that cover the whole range of conservation compatibility. We showthat in the analyzed case heritage preservation is compatible with a four-fold reduction in energy needs at a high thermal comfort level. Even higher energy savings are only achievable at the cost of heritage degradation.

机器人抛光M-ZnS去除函数建模与工艺参数优化

为研究M-ZnS在机器人抛光过程中的材料去除模型和优化参数组合,探究M-ZnS光学元件的高精度、低成本、批量化制造方案,采用有限元法和数值仿真法,对M-ZnS的机器人抛光材料去除函数模型进行修正。基于有限元法建立了抛光盘的压力分布模型,采用曲线拟合方法得到了压力分布函数。仿真模型和实验数据对比表明,去除函数模型与实验数据中心相对偏差小于8%,证实了修正去除函数模型的有效性。然后,对抛光关键工艺参数进行优化,通过单因素实验法,获得了机器人抛光M-ZnS的优化工艺参数组合:对于10 mm的沥青盘,推荐压力为0.12~0.18 MPa,推荐的转速比为200/-10~200/-50 r/min。最后,采用修正的去除函数模型和优化工艺参数对100 mm口径的M-ZnS平面光学元件进行抛光,并对抛光前后的表面粗糙度和面形精度进行测量和对比。实验结果表明,经过单轮80.39 min抛光,表面质量明显提高,元件淡黄色逐渐褪去,表现为透明材料,面形PV从0.668μm降至0.229μm,收敛率为65%,表面粗糙度Sa从7.911 nm降低至2.472 nm,收敛率为68%。机器人抛光技术可作为M-ZnS光学元件高效高质量加工的重要手段。

Book Review “William R. Spillers and Keith M. MacBain. Structural Optimization,Springer Dordrecht Heidelberg London New York,2009”

This book presents general theories and applications of structural optimization methods. The first chapter of the book introduces various basic concepts of structural optimization through several illustrative examples. Chapter 2 is devoted to a comprehensive review of math- ematical programming methods, including classical methods such as the simplex method, the （SLP） method, the interior point method and relatively new approaches such as genetic algo- rithms. The third chapter presents the main topic of this book, the SLP methods based on the incremental equations of structures. Some useful techniques in implementation of SLP, including the move limit, scaling and active constraint identifying, are discussed. In chapter 4, classical optimality criterion approaches, including the fully stress approach for truss struc- tures and its extensions for membrane and plate structures, are presented with demonstrative examples. The remaining chapters develop an overview of structural optimization problems, among which are dynamic optimization, multi-criterion optimization, earlier work on the op- timal layouts of plates, as well as some practical issues in general size and shape optimization problems.

Optimization of High Power 1.55-μm Single Lateral Mode Fabry-Perot Ridge Waveguide Lasers

Optimization of the high power single-lateral-mode double-trench ridge waveguide semiconductor laser based on InGaAsP/InP quantum-well heterostructures with a separate confinement layer is reported. Two different waveguide structures of Fabry-Perot lasers emitting at a wavelength of 1.55 μm are fabricated. The influence of an effective lateral refractive index step on the maximum output power is investigated. A cw single mode output power of 165mW is obtained for a 1-mm-long uncoated laser.

Forecasting Multi-Step Ahead Monthly Reference Evapotranspiration Using Hybrid Extreme Gradient Boosting with Grey Wolf Optimization Algorithm

It is important for regional water resources management to know the agricultural water consumption information several months in advance.Forecasting reference evapotranspiration(ET_(0))in the next few months is important for irrigation and reservoir management.Studies on forecasting of multiple-month ahead ET_(0) using machine learning models have not been reported yet.Besides,machine learning models such as the XGBoost model has multiple parameters that need to be tuned,and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution.This study investigated the performance of the hybrid extreme gradient boosting(XGBoost)model coupled with the Grey Wolf Optimizer(GWO)algorithm for forecasting multi-step ahead ET_(0)(1-3 months ahead),compared with three conventional machine learning models,i.e.,standalone XGBoost,multi-layer perceptron(MLP)and M5 model tree(M5)models in the subtropical zone of China.The results showed that theGWO-XGB model generally performed better than the other three machine learning models in forecasting 1-3 months ahead ET_(0),followed by the XGB,M5 and MLP models with very small differences among the three models.The GWO-XGB model performed best in autumn,while the MLP model performed slightly better than the other three models in summer.It is thus suggested to apply the MLP model for ET_(0) forecasting in summer but use the GWO-XGB model in other seasons.

基于VMD-DBO-LSTM的空气质量预测

针对传统空气质量预测模型收敛速度慢,精度低的问题,提出一种基于变分模态分解(variational mode decomposition,VMD)和蜣螂优化算法(dung beetle optimizer,DBO)优化长短期记忆网络(long short term memory,LSTM)的预测模型。首先,针对AQI原始数据具有大量噪声的问题,使用VMD方法对非平稳信号进行模态分解以降低噪声对预测结果的影响从而获得多个不同特征的模态分量;其次,针对LSTM靠人工经验调参存在一定局限性,利用DBO算法对LSTM模型参数进行优化;最后,对分解后的各个子序列使用LSTM模型预测,将各个子序列进行叠加得到最后的预测结果。实验结果表明,VMD对非平稳数据的分解有助于提高预测精度,VMD-DBO-LSTM模型的性能较其他模型均有不同程度的提高,该模型预测的均方根误差为4.73μg/m^(3),平均绝对误差为3.61μg/m^(3),拟合度达到了97.8%。

Optimization of 1.3-μm InGaAsP/InP Electro-Absorption Modulator

We report the simulation and experimental results of 1.3-μm InGaAsP/InP multiple quantum well （MQW） electro-absorption modulators （EAMs）. In this work, the quantum confined Stark effect of the EAM is system- atically analyzed through the finite element method. An optimized structure of the 1.3-μm InGaAsP/InP QW EAM is proposed for applications in 100 G ethernet. Then 1.3-μm InGaAsP/InP EAMs with f-3dB bandwidth of over 20 GHz and extinction ratio over 20 dB at 3 V bias voltage are demonstrated.

基于RCC-M规范建造的核电站一回路水压试验工艺优化研究

就ASME和RCC-M两种体系标准关于压力试验的技术差异开展了溯源研究,结合断裂力学计算结果与压力爆破试验数据对水压试验的目的和能力进行了分析,通过论述超声技术的发展和研究一回路边界完整性,得出泄漏试验替代水压试验对一回路完整性不会带来负面影响的结论。

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Nonlinear optimal model and solving algorithms for platform planning problem in battlefield

Platform planning is one of the important problems in the command and control(C2) field. Hereto, we analyze the platform planning problem and present nonlinear optimal model aiming at maximizing the task completion qualities. Firstly, we take into account the relation among tasks and build the single task nonlinear optimal model with a set of platform constraints. The Lagrange relaxation method and the pruning strategy are used to solve the model. Secondly, this paper presents optimization-based planning algorithms for efficiently allocating platforms to multiple tasks. To achieve the balance of the resource assignments among tasks, the m-best assignment algorithm and the pair-wise exchange(PWE)method are used to maximize multiple tasks completion qualities.Finally, a series of experiments are designed to verify the superiority and effectiveness of the proposed model and algorithms.

A Novel Stochastic Framework for the Optimal Placement and Sizing of Distribution Static Compensator

This paper proposes a new stochastic framework based on the probabilistic load flow to consider the uncertainty effects in the Distribution Static Compensator (DSTATCOM) allocation and sizing problem. The proposed method is based on the point estimate method (PEM) to capture the uncertainty associated with the forecast error of the loads. In order to explore the search space globally, a new optimization algorithm based on bat algorithm (BA) is proposed too. The objective functions to be investigated are minimization of the total active power losses and reducing the voltage deviation of the buses. Also to reach a proper balance between the optimization of both the objective functions, the idea of interactive fuzzy satisfying method is employed in the multi-objective formulation. The feasibility and satisfying performance of the proposed method is examined on the 69-bus IEEE distribution system.

基于改进M-P法的坡态控制参数优化设计

为研究坡态控制参数与边坡安全系数之间的非线性关系及弥补传统Morgenstern-Price(M-P)法的缺陷,基于陈冲砂岩矿露天采场边坡工程,提出了坡态优化设计方案。引入时程法对传统M-P法进行改进,计算了不同设计方案下的边坡安全系数,探讨了边坡安全系数衰减规律及递增规律,最终确定出最佳设计方案。结果表明:原设计方案中,边坡最危险时刻为28 ms,此时的边坡安全系数为1.057;在边坡安全系数减速衰减阶段安全系数平均降低了3.38%,在加速衰减阶段安全系数平均降低了5.68%;台阶坡面角越大,边坡稳定性受台阶宽度的影响越大,不同台阶坡面角下安全系数分别增加了10.0%、10.4%、10.5%、10.6%、10.6%;相比原设计方案,最优设计方案中安全平台宽度增加了1 m,清扫平台宽度增加了2 m,台阶坡面角减少了6°。

Recent developments in optimal experimental designs for functional magnetic resonance imaging

Functional magnetic resonance imaging(fMRI)is one of the leading brain mapping technologies for studying brain activity in response to mental stimuli.For neuroimaging studies utilizing this pioneering technology,there is a great demand of high-quality experimental designs that help to collect informative data to make precise and valid inference about brain functions.This paper provides a survey on recent developments in experimental designs for fMRI studies.We briefly introduce some analytical and computational tools for obtaining good designs based on a specified design selection criterion.Research results about some commonly considered designs such as blocked designs,and m-sequences are also discussed.Moreover,we present a recently proposed new type of fMRI designs that can be constructed using a certain type of Hadamard matrices.Under certain assumptions,these designs can be shown to be statistically optimal.Some future research directions in design of fMRI experiments are also discussed.

基于M-NSGA-Ⅱ的转炉炼钢补加供料量优化

在转炉炼钢过程中,供料量的多少会极大影响钢水的终点碳含量和终点温度,因此,优化转炉炼钢的补加供料量可以提高钢铁的产出质量。首先,依据二次吹炼终点碳温与补加供料量的回归模型构建了补加供料量优化模型;其次,由于转炉炼钢要求优化算法的计算时间短,设计了移动非支配排序遗传算法Ⅱ(movingnon-dominatedsortinggenetic algorithm Ⅱ, M-NSGA-Ⅱ);最后,采用目标函数平均缩小值与平均标准差作为评价指标,对模型结果进行对比实验。结果表明,所设计的M-NSGA-Ⅱ可以在较短的计算时间内获得更优的非支配解集,并且基于该算法的补加供料量优化模型可以有效调整终点碳温。

M型预制袋袋口折合机构运动精度可靠性优化

目的为提高M型预制袋包装机袋口折合机构轨迹输出点的运动精度,对袋口折合机构进行运动精度可靠性优化。方法在运动学分析的基础上,用环路增量法建立考虑杆长误差时袋口折合机构的位置误差模型,接着对轨迹输出点进行可靠性分析及蒙特卡洛法验证,通过灵敏度分析确定关键误差影响因素,最后进行运动精度可靠性优化。结果建立的可靠性模型可以有效地反映杆长误差对机构运动精度的影响,x分量轨迹的可靠度由82.5%提高至92.91%,y分量轨迹可靠度由65.34%提高至89%。结论经过可靠性优化能够使袋口折合机构运动精度满足设计要求。

直径11.36 m盾构车行隧道空间优化后的同层疏散检修救援模式探索

结合11.36 m直径隧道案例分析,通过空间优化设计布局,将其原本传统的上层车道、下层疏散检修的固有模式改变为同层疏散检修救援模式。同时,优化人行横通道设置,建设、设计、运管和使用习惯更加匹配合理。

基于净能力及二阶锥规划的分布式光储多场景协同优化策略

针对现有配电网中分布式光储调度模型存在资源协同不足、求解复杂等问题,提出了一种基于净能力及二阶锥规划的分布式光储多场景协同优化调度策略。通过引入储能接入配电网后的功率转移分布因子,提出一种基于系统净能力的储能最优选址计算方法;综合考虑储能的运行特性和分布式光伏的出力不确定性,建立以系统日综合成本和削峰填谷为目标的分布式光储多场景协同优化调度模型;利用二阶锥松弛和Big-M法对潮流约束、储能运行约束进行处理,将原规划模型转化为混合整数二阶锥规划问题。以IEEE 33节点系统和西北某实际系统为算例进行仿真分析,结果表明所提方法能在降低负荷峰谷差和日综合成本、平抑负荷波动的同时,显著提高对分布式光伏的消纳能力,验证了所提方法的有效性和可行性。

基于排队论的某食品零售店收银系统优化研究

对于某食品零售店高峰期排队结账时间较长的问题,提出两种针对性的解决方案。通过选取节假日客流高峰时间段的数据进行现场采集,基于运筹学中的排队理论对该食品零售门店高峰期两小时的实际客流进行统计,运用python建立M/G/2模型,利用真实数据进行模拟仿真,根据仿真结果提出两种可行的优化方案,并对优化方案进行仿真计算。计算结果表明,不论是收银系统的改变还是排队模式的改变,都能够更加充分地利用环境资源、硬件资源和人力资源,能帮助该类门店缓解高峰时期客流拥堵的现象,由此见得,优化后的系统相较于优化前更加高效合理。这样门店就能够将更好的服务提供给消费者,从而提高消费者的满意程度,为企业带来更大的效益,门店可以根据实际情况安排合适的优化方式。

基于Google earth engine渭-库绿洲果园遥感提取

针对干旱区果园大面积遥感提取困难、识别精度低等问题,本研究基于GEE(Google earth engine)平台,综合应用Sentinel-1/Sentinel-2影像构建特征集。通过对比原始特征组合、Jeffries-Matusita(J-M)距离、属性重要度3种优化方式,结合随机森林(Random forest,RF)分类方法,对比得到最佳优化方式,探索果园最优分类特征集。结果表明:识别效果最好的方案为G17 JM,总体精度为91.25%,kappa系数为0.89,面积精度为82.55%。最优特征集为B8_asm、B8_ent、B8_idm、NDVI re3、B6、B7、a、e、b、EVI、B11、B8A、B8、VV。使用J-M距离进行特征集优化,有效降低数据量、提高计算效率,更有利于精确遥感识别果园种植面积。表明GEE快速、准确获取果园种植面积的可行性,为获取果园动态变化提供强有力的基础。

基于L-M优化算法的BP神经网络的作物需水量预测模型

应用L-M优化算法BP神经网络,通过多维气象数据(太阳辐射、空气温度、湿度)与作物需水量的相关分析,来确定网络的拓扑结构,建立作物需水量的人工神经网络模型。用美国田纳西州大学高原实验室所测的100d气象数据为输入、作物需水量为输出来训练建立好的BP神经网络,仿真表明该神经网络能很好地解决需水量多影响因素之间的不确定性和非线性,模型的预测精度较高,同时通过一组非样本天气环境参数和作物需水量来验证该神经网络,也得到了较好的预测结果,能够满足灌溉的精度要求。