富水软岩巷道稳定性控制技术研究

富水条件下软岩巷道容易出现大变形及围岩强度大幅度降低等情况,对矿井的生产安全造成极大威胁。为探索富水软岩巷道稳定性控制技术,结合新上海一号煤矿113082工作面运输巷工程实例,采用理论分析方法研究了地下水对巷道围岩及支护结构的影响,提出围岩稳定性控制对策,并对控制方案进行数值模拟验证。针对富水软岩巷道,首先采取导、疏结合的控水措施,减小对原有围岩强度的影响,降低对支护结构的损害;其次采用全断面、多手段联合加固的支护措施,控制围岩变形。工程实际及数值模拟结果表明,对于富水软岩巷道采取以上技术措施,能够有效保证巷道的稳定性。     

An optimization algorithm for the workforce management in a retail chain

This work proposes a scheduling problem for the workforce management in a chain of supermarkets operating in Italy. We focus on determining the ideal mix of full-time and part-time workers which are needed every week to guarantee a satisfactory service level during the check-out operations. The generation of working shifts, to be assigned to retail workers, is subject to several constraints imposed by both labour laws and enterprise bargaining agreements.We present a mathematical formulation of the problem followed by an exact solution approach which relies on the definition of feasible daily working shifts. The number of feasible daily shifts, that are combined to determine feasible weekly shifts, could drastically increase, depending on the selected planning interval. In addition, there may exist additional constraints, that are difficult to incorporate into the mathematical model. For these reasons, a hybrid heuristic, which does not require the generation of all feasible weekly shifts, is proposed in this paper.Using appropriate statistical techniques, a sensitivity analysis is performed to test the design of the hybrid heuristic. Computational tests are carried out by solving several real instances provided by the retail firm. The results obtained by the heuristic are compared both with an exact approach and with the solutions adopted by the retail company, which have been determined by using a naïf approach. Our hybrid heuristic exhibits excellent performance finding optimal or near optimal solutions in a very limited CPU time.     

Hybrid tabu search and a truncated branch-and-bound for the unrelated parallel machine scheduling problem

We consider the problem of scheduling a number of jobs on a number of unrelated parallel machines in order to minimize the makespan. We develop three heuristic approaches, i.e., a genetic algorithm, a tabu search algorithm and a hybridization of these heuristics with a truncated branch-and-bound procedure. This hybridization is made in order to accelerate the search process to near-optimal solutions. The branch-and-bound procedure will check whether the solutions obtained by the meta-heuristics can be scheduled within a tight upper bound. We compare the performances of these heuristics on a standard dataset available in the literature. Moreover, the influence of the different heuristic parameters is examined as well. The computational experiments reveal that the hybrid heuristics are able to compete with the best known results from the literature.     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

Optimal scheduling of single stage batch plants with direct heat integration

This paper addresses the multi-objective optimization problem arising in the operation of heat integrated batch plants, where makespan and utility consumption are the two conflicting objectives. A new continuous-time MILP formulation with general precedence variables is proposed to simultaneously handle decisions related to timing, product sequencing, heat exchanger matches (selected from a two-stage superstructure) and their heat loads. It features a complex set of timing constraints to synchronize heating and cooling tasks, derived from Generalized Disjunctive Programming. Through the solution of an industrial case study from a vegetable oil refinery, we show that major savings in utilities can be achieved while generating the set of Pareto optimal solutions through the ɛ-constraint method.     

A systemic framework and analysis of urban water energy

Energy impacts of urban water systems are substantial, but not typically analysed systemically. We develop a new system boundary framework including a utility, the ‘bulk water supply authority’ (SB1); the ‘urban water system’ including water use (SB2); and the ‘regional water system’ (SB3). We use the framework to review existing models and show that most address only one boundary. We apply the framework to quantify thermal equivalents of water-related energy in SB1 and SB2, and identify that over 96% of water-related energy in South East Queensland (SEQ) is outside SB1 and within SB2. Consideration of energy influenced by water use is paramount to systemic energy efficiency and optimisation in the urban water system. Clear articulation of system boundaries will improve modelling and management of the energy impact of urban water. Systemic modelling will help decision makers answer increasingly integrated and cross-system and sector questions regarding water and energy interactions.     

Traumatic brain injury,driver aggression and motor vehicle collisions in Canadian adults

ObjectiveThis study examines the associations between lifetime traumatic brain injury (TBI), driver aggression, and motor vehicle collisions among a population sample of adults who reside in the province of Ontario, Canada.MethodA cross-sectional sample of 3993 Ontario adults, aged 18–97 were surveyed by telephone in 2011 and 2012 as part of Center for Addiction and Mental Health’s ongoing representative survey of adult mental health and substance use in Canada. TBI was defined as trauma to the head that resulted in loss of consciousness for at least five minutes or overnight hospitalization.ResultsAn estimated 91% (95% CI: 90.0, 91.9) of individuals in this sample held a valid Ontario driver’s license at the time of testing. Among those, 16.7% reported a history of lifetime TBI and 83.3% reported no TBI. The prevalence of TBI was higher among men than women. Relative to licensed adults without TBI, adults with a history of TBI had significantly higher odds of engaging in serious driver aggression in the past 12 months, such as making threats to hurt another driver, passenger or their vehicle (AOR = 4.39). These individuals also reported significantly higher odds (AOR = 1.74) of being involved in a motor vehicle collision that resulted in hurting themselves, their passenger(s) or their vehicle.ConclusionThis is the first population-based study to demonstrate a relationship between a history of TBI and higher rates of serious driver aggression and collision involvement. Given the large proportion of adult drivers with a history of TBI, these individuals may account for a disproportion burden of all traffic safety problems. Whether the increased road safety risk of adults with a history of TBI is reflective of neurocognitive deficits or is merely evidence of a cluster of unsafe activities produced by a higher risk lifestyles requires further research attention.     

A web-based screening model for climate risk to water supply systems in the northeastern United States

The aim of this study is to describe the development and application of a web-based decision support tool (ViRTUE) for performing climate risk evaluations of water supply systems. The tool is designed for small-scale water utilities in the northeastern United States that may lack the resources for detailed climate change risk investigations. Development of this tool demonstrates a relatively new approach to web application development using the Shiny framework for the R programming language to create an interactive environment for stakeholders and water managers to explore climate vulnerabilities. Using a decision-scaling framework, the tool allows the user to perform a climate stress test to evaluate the performance and vulnerability to water supply shortfalls of local reservoir systems over a wide range of potential climate change scenarios using a generic systems model. Probabilities of future climate conditions derived from climate projections then help inform utility operators of impending risk.     

Systematic tool to plan and evaluate demand side strategies during sustained energy crises in hydrothermal power systems

HARE, a systematic tool to evaluate demand side measures to face sustained energy supply risk in hydrothermal power systems is presented in this paper. The main focus of the paper is to help centralized planners to systematically discuss, select, and plan the measures that better respond to the variety of critical situations that can arise due to expected energy shortage, integrate them into the usual medium-term scheduling tool and consequently keep the associated overall costs as low as possible. A medium-term definition of the system state is proposed as a decision-making aid, as well as a set of general energy saving measures that can be applied with their corresponding attributes (time delays, costs of implementation, and energy saving impact). The tool is demonstrated and applied to a simplified version of Chilean’s medium-term hydrothermal scheduling model and to a specific risk scenario experienced during 2011. The results show that it is possible to define various sets of demand side measures that avoid the impacts on the system and subsequently to select among them those with least expected implementation costs. This tool seems mainly useful for hydro-electric systems, which are more vulnerable to sustained energy supply risk. Every power system will have to go through a detailed review and planning process to implement this type of tool.