Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level

Energy efficiency and environmental performance optimization at the district level are following an upward trend mostly triggered by minimizing the Global Warming Potential (GWP) to 20% by 2020 and 40% by 2030 settled by the European Union (EU) compared with 1990 levels. This paper advances over the state of the art by proposing two novel multi-objective algorithms, named Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Harmony Search (MOHS), aimed at achieving cost-effective energy refurbishment scenarios and allowing at district level the decision-making procedure. This challenge is not trivial since the optimisation process must provide feasible solutions for a simultaneous environmental and economic assessment at district scale taking into consideration highly demanding real-based constraints regarding district and buildings’ specific requirements. Consequently, in this paper, a two-stage optimization methodology is proposed in order to reduce the energy demand and fossil fuel consumption with an affordable investment cost at building level and minimize the total payback time while minimizing the GWP at district level. Aimed at demonstrating the effectiveness of the proposed two-stage multi-objective approaches, this work presents simulation results at two real district case studies in Donostia-San Sebastian (Spain) for which up to a 30% of reduction of GWP at district level is obtained for a Payback Time (PT) of 2–3 years.Part of this work has been developed from results obtained during the H2020 “Optimised Energy Efficient Design Platform for Refurbishment at District Level” (OptEEmAL) project, Grant No. 680676

A novel computer aided engineering method for comparative evaluation of nonlinear structures in the conceptual design phase

Selection of the preferred design concept during design represents a major challenge to design engineers as the required level of information and rigour to achieve an objective evaluation at early stage of design is typically not available. This is particularly evident during evaluation of design concepts of complex load-bearing mechanical structures. The engineering design concepts during concept design phase typically lack detail and more specific performance indicators to enable accurate evaluation. Hence in such cases, a prevailing evaluation approach is based primarily on qualitative scores inferred through personal intuition and historical experience of the design team or individual experts. The principal motivation behind this research is to improve the ability and confidence to select a superior design concept early in the design process. The conventional approach is sensitive to individual expertise and availability of experienced designers. Therefore, in order to make more informed decisions especially in case of complex engineering designs, the concept evaluation methods require more detailed and accurate information. This research is concerned with the development of a novel method for comparative evaluation of engineering design concepts that exhibit nonlinear structural behaviour under load. The approach is based on two key concepts: i) an expansion of the conventional substructuring technique into the nonlinear domain to enable FEA to be more applicable, effective and computationally affordable in early stages of the conceptual design phase; and ii) a restructuring of the traditional process by incorporating the optimisation search to provide orderly rule-guided evolution of design concepts in order to produce objective development metrics which alleviates the dependence on personal intuition and historical experience of the engineering designers. A series of experiments and validation case studies conducted in this research provide conclusive evidence that demonstrates the applicability and the significance of the developed method in terms of reduced time for evaluation and amount of recurrent knowledge generated compared to the more traditional approaches based on the application of FEA in the conceptual design phase. Furthermore, a Confidence Index as a performance measure is developed in this research to describe the quality of the obtained solutions. The derived Confidence Index is a novel contribution to the fields of metaheuristic measurements and engineering concept validation methodology

Research in Structures and Dynamics, 1984

A symposium on advanced and trends in structures and dynamics was held to communicate new insights into physical behavior and to identify trends in the solution procedures for structures and dynamics problems. Pertinent areas of concern were (1) multiprocessors, parallel computation, and database management systems, (2) advances in finite element technology, (3) interactive computing and optimization, (4) mechanics of materials, (5) structural stability, (6) dynamic response of structures, and (7) advanced computer applications

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership

Comparative assessment of implicit and explicit finite element solution schemes for static and dynamic civilian aircraft seat certification (CS25.561 and CS25.562)

Due to the competitive nature of airline industry and the desire to minimise aircraft weight, there is a continual drive to develop lightweight, reliable and more comfortable seating solutions, in particular, a new generation slim economy seat. The key design challenge is to maximise the “living space” for the passenger, with strict adherence to the ‘Crash Safety Regulations’. Cranfield University is addressing the needs of airliners, seat manufactures and safety regulating bodies by designing a completely novel seat structure coined as “Sleep Seat”. A generous angle of recline (40 degree), movement of “Seat Pan” along the gradient, fixed outer shell of the backrest, and a unique single “Forward Beam” design distinguishes “Sleep Seat” form current generation seats. It is an ultra-lightweight design weighing 8kg (typical seat weight is 11kg). It has to sustain the static (CS 25.561) and dynamic (CS25.562) “Emergency landing” loads as specified by “Certification Specifications (CS). Apart from maintaining structural integrity; a seat-structure must not deform, which would impede evacuation, should absorb energy so that the loads transferred to Occupants are within human tolerance limits and should always maintain survivable space around the Occupant. All these parameters, which increase a life-expectancy in a ‘survivable’ crash, can be estimated using either experimental testing or virtual simulation tools such as “Finite Element Analysis (FEA). Design of the “Sleep Seat” is still in its conceptual phase and therefore experimental testing for all the design iterations involved is unrealistic, given a measure of the costs and timescales involved. Therefore focus of research is to develop practical and robust FE methodologies to assess static and dynamic performances of a seat-structure so as to compare different design concepts based on their strength, seat interface loads (a limit defined by strength of aircraft-floor), maximum deformations and cross-sectional forces ... [cont.]

Minimizing the sum of flow times with batching and delivery in a supply chain

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of this thesis is to study one of the classical scheduling objectives that is of minimizing the sum of flow times, in the context of a supply chain network. We consider the situation that a supplier schedules a set of jobs for delivery in batches to several manufacturers, who in tum have to schedule and deliver jobs in batches to several customers. The individual problem from the viewpoint of supplier and manufacturers will be considered separately. The decision problem faced by the supplier is that of minimizing the sum of flow time and delivery cost of a set of jobs to be processed on a single machine for delivery in batches to manufacturers. The problem from the viewpoint of manufacturer is similar to the supplier's problem and the only difference is that the scheduling, batching and delivery decisions made by the supplier define a release date for each job, before which the manufacturer cannot start the processing of that job. Also a combined problem in the light of cooperation between the supplier and manufacturer will be considered. The objective of the combined problem is to find the best scheduling, batching, and delivery decisions that benefit the entire system including the supplier and manufacturer. Structural properties of each problem are investigated and used to devise a branch and bound solution scheme. Computational experience shows significant improvements over existing algorithms and also shows that cooperation between a supplier and a manufacturer reduces the total system cost of up to 12.35%, while theoretically the reduction of up to 20% can be achieved for special cases

New Model for Bridge Management System (BMS): Bridge Repair Priority Ranking System (BRPRS), Case Based Reasoning for Bridge Deterioration, Cost Optimization, and Preservation Strategy

Most public transportation agencies (Such as, state department of transportations (DOTs) and department of public works for cities and towns.) in the United States are constantly pursuing ways to improve bridge asset management to optimize their use of limited available funds for rehabilitation, replacement, and preventive maintenance. Given the realities of available funding, there is a significant difference between available funds and funds required for maintaining bridges in good condition. The proper preventative maintenance and treatments should be performed at the right time to be cost effective and extend the life of bridges. Neglecting maintenance can cause higher future costs and further deteriorate the conditions that will increase the risk of bridge closure. This would require complete or partial replacement as well as additional funds needed for detours and traffic control which interrupts services to the motorist and creates more congestion. Development and implementation of a Bridge Management System (BMS) provide states and municipalities with a tool to help identify maintenance repair, prioritize bridge rehabilitation and replacement, develop preservation strategies, and allocate available funds accordingly. The primary objective of this research is to develop a Bridge Management System (BMS) to manage municipal and state bridge assets. Complete, accurate data in well-designed form is vital to a Bridge Management System (BMS). This system will make available work reports, engineering drawings, photographs, and a forecasting model for management staff use. Inventory and condition data are extracted from the U.S. Federal Highway Administration (FHWA) and National Bridge Inventory System (NBIS) coding guidelines. The proposed model provides: (1) A priority ranking system for Rehabilitation and Replacement projects, which enables the decision-makers to understand and compare the overall state of all the bridges in the network. It embraces seven factors condition, criticality, risk, functionally, bridge type, age, and size. (2) A deterioration model that uses optimized case-based reasoning (CBR) method. A similarity measure of classification is developed to identify how close the characteristics of bridge components are to each other based on a scoring system. (3) A cost model that considers different repair strategies and provide bridge repair recommendations with estimated cost repairs. (4)The model feeds data to a forecasting program that prepares 120-year preservation, maintenance, repair and rehabilitation budgets and schedules to sustain a bridge network at the highest performance level under approved budgets. The forecasting option contains default management costs that are upgraded as work report data yields costs based on locality and individual bridge projects. BMS will give accessibility through linkages to all available municipal, and DOT, bridge data in the state. The data will be available through ArcGIS on tablets, laptops, and smartphones with access to cloud storage