Farayi Musharavati

A Review on Fatigue Life Prediction Methods for Metals

Metallic materials are extensively used in engineering structures and fatigue failure is one of the most common failure modes of metal structures. Fatigue phenomena occur when a material is subjected to fluctuating stresses and strains, which lead to failure due to damage accumulation. Different methods, including the Palmgren-Miner linear damage rule- (LDR-) based, multiaxial and variable amplitude loading, stochastic-based, energy-based, and continuum damage mechanics methods, forecast fatigue life. This paper reviews fatigue life prediction techniques for metallic materials. An ideal fatigue life prediction model should include the main features of those already established methods, and its implementation in simulation systems could help engineers and scientists in different applications. In conclusion, LDR-based, multiaxial and variable amplitude loading, stochastic-based, continuum damage mechanics, and energy-based methods are easy, realistic, microstructure dependent, well timed, and damage connected, respectively, for the ideal prediction model.

Synthesis, characterization, and properties of nickel–cobalt layered double hydroxide nanostructures

Nickel–cobalt layered double hydroxides (Ni–Co-LDH) have recently been examined for their potential as battery-type hybrid supercapacitors made from metal hydroxide electrode materials, due to their unique spatial structure, excellent electrochemical activity, and good electrical conductivity. However, the main disadvantage restricting the application of Ni–Co-LDHs is their low electronic conductivity, which results in low capacitance. To address this problem, we used different concentrations of ammonium fluoride to control the Ni–Co-LDH surface morphology and direct growth on Ni foam (NF). We created Ni–Co-LDH composite electrode materials with different morphologies that showed large surface areas, high conductivity, and high electrochemical performance. Results showed that the samples prepared with ammonium fluoride additive had a higher specific capacity of about 1445 F g−1 at a current density of 2 A g−1, a good specific capacitance rate of about 59.5% from 2 A g−1 to 40 A g−1, and good capacity retention of up to 99% when the current density was enhanced to 30 A g−1, suggesting promise for future applications.

Building thermal energy modeling with loss minimization

Abstract The thermal losses in buildings are significant energy sinks. The Energy Semantic Network (ESN) is a new method for finding these losses at the design stage, as well as for the existing structures. The research purpose of ESN is to take into consideration the governing factors of building thermal performance (i.e. the insulation materials, the dimensions, the loads, and the schedules of people interactions), associate these factors with any building of choice, and to subject the model to range of dynamical changes, that will help to make the decisions for improving the building thermal performance. The current work is only an early stage on ESN, the end goal of ESN is to evaluate the thermal energy conservation technologies with respect to the dynamical thermal changes, and track the dominant sinks resulting from these changes. Currently, the energy conservation technologies present an opportunity for reducing the utility use, and, thereby, the savings in capital for long term performance. The thermal energy conservation problems are unique to every building, due to the storage and the supply of the energy in response to the seasonal demands, structure, and the nature of the building utilization (the involvement of people). With the current simulation software, such as Energy Plus, there exists a convenient way of simulating the annual building performance, without the tediousness of monitoring the physical building. However, in that case, any particular spontaneous effects may not be completely accounted. The ESN structure is intended to make up for the spontaneous effects, and be accountable for possible spikes in the energy use that may occur throughout the year. Such spikes in energy consumption do not have to be singular, because it is possible to assign an array of situations where energy losses occur and track them to the specific location. The use of ESN for tracking the energy losses can lead to a solution for preventing similar spikes in the future by isolating the most significant sink. The enclosed research on the ESN method includes the foundations of ESN, the case study of a hypothetical hotel located in Ontario, and a detailed Simulink representation of ESN.

Key performance indicators (KPIs) for evaluation of energy conservation in buildings

The main objectives of this paper are to: identify key performance indicators (KPIs) related to intelligent buildings (economical, environmental, reliability, and quality), and; propose a simulation framework for evaluation of these KPIs. Energy simulation of a building is a key to study the energy efficiency in the building. This paper presents an integrated framework based on Google™ SketchUp, OpenStudio, ResultViewer, and EnergyPlus software for energy simulation of a large hotel building with different types of energy zones, loads schedules, and set-points. The aim of this paper is to calculate some important KPIs in a building environment to access the overall efficiency of the building.

Operations optimization towards high performance cooling in commercial buildings

In this paper, an analysis and evaluation of the operations of a typical shopping mall in Qatar was carried out. The aim is to optimize operations towards high energy performance with respect to cooling energy. For the study, a comparison of the energy consumption of two cooling system operation strategies, i.e., scheduled and unscheduled district cooling, for the shopping mall was conducted. Building operations strategies for improving cooling performance were identified, analyzed, simulated and evaluated. The study shows variations in the various performance measures associated with the cooling performance. A number of operational factors for optimizing cooling efficiency and effectiveness were identified and simulated. Simulation results show that building operations that focus on energy savings significantly contribute to high energy performance in commercial buildings. The analysis also showed that scheduling district cooling can result in 12.89% total annual energy savings.

Dynamic aggregated building electricity load modeling and simulation

In order to support the growing interest in demand response modeling and analysis, there is a need for physical-based building load models. This work presents a new approach for simulating electrical power flow in buildings. The new approach handles the power flow capacity shortage in existing building simulation programs, which have been used for the past few decades by building energy communities. The suggested approach represents the building as a group of electrical networks, organized in hierarchical levels. On the top level, the user defines key parameters such as rated power and power factor of existing loads. The power cables are modeled by their equivalent PI model. Accurate simulation models are developed for solving the building network equations where building loads are integrated into building network. Smart meters are implemented at different locations for power quality and energy auditing. Two case studies of residential and commercial buildings are investigated to prove the capability of the introduced approach. A comparison with EnergyPlus, as verified building energy software, is introduced to prove the ability of the proposed Matlab-based model to evaluate the annual energy consumption of the building. All results show the accuracy and ability of the proposed approach for simulating the electrical power flow of the building and can be integrated with renewable and storage energy.

Energy Savings Through Applications of Lean Manufacturing Principles

This study explores and investigates the applicability of lean manufacturing principles and concepts in Dual Purpose Water and Electricity (DPWE) production plants. An existing DPWE production plant in the State of Qatar was used as a case study. The aim of the investigation was to identify opportunities for energy savings by analyzing plant energy use through Lean Value Stream Mapping. To this end, lean principles were employed to investigate energy wastes in the power and water production chains. ‘Lean deadly wastes’ were used to identify potential ‘wastes’ along the DPWE production system. Tools and techniques for analyzing, evaluating, and assessing energy use in the DPWE production plant were developed. Areas of energy wastes along the process system were identified and lean concepts were applied to reveal quick, non-capital energy saving opportunities. Energy assessments were carried out through the value stream mapping method that helped in the identification and detection of energy and operating efficiency improvement opportunities. The multi-stage flash distillation process was identified as the section that consumed relatively the largest energy. Other energy efficiency opportunities were revealed by virtually reconfiguring the DPWE production plant in the framework of lean principles and concepts. Results of the case study shows that a number of energy saving opportunities and energy efficiency initiatives exist in the various sections of the DPWE production plant. Therefore, lean principles are powerful concepts that can help in identifying energy saving opportunities and energy efficiency initiatives in DPWE production plants. Such opportunities and initiatives can be implemented to improve operating efficiencies and reduce production costs with the added advantage of improved environmental performance.

High temperature thermal stability of innovative nanostructured thin coatings for advanced tooling

Tools for machining are made of hard steels and cemented carbide (WC-Co). For specialized applications, such as aluminium machining, diamond or polycrystalline cubic boron nitride are also used. The main problem with steel, isthat itexhibits a relatively low hardness (below 10 GPa) which strongly decreases upon annealing above about 600 K.Thus, the majority of modern tools are nowadays coated with hard coatings that increase the hardness, decrease the coefficient of friction and protect the tools against oxidation. A similar approach has been recently used to obtain a longer duration of the dies for aluminium die-casting.

Thermal Plasticity Index of Nanostructured N-Based Coatings on HSS 6-5-2 (1.3343) Tool Steel

Nowadays, cutting tools, designed to be used for machining without lubricants, are developed to improve the high working speed capabilities. With this respect, quaternary Ti-and N-based coatings are able to significant increase hardness, wear resistance and high temperature oxidation resistance. One of the major drawbacks still consists on the limited thermal stability of such coatings, which is reported to be about 600°C. In the present study, thermal stability studies of a nanostructured multi-layered N-based (AlTiCrxN1-x) coating on a HSS 6-5-2 tool steel were carried out. Two quantities were calculated out of the hardness and elastic modulus of the coatings. One is the ratio H/E that represents the coating resistance to compression without failure; another one is H3/E2, which provides information on the specific contact pressure limit without failure. It was found that, by using the less demanding thermal cycling mode, the coating ability to plastically deform without damage, is retained up to 800-1000°C. The highest, and more effective coating plasticity index was obtained by using the less demanding cycling mode, while, the other two modes induced a continuous index decrease with temperature.

Corrigendum to “Dynamic aggregated building electricity load modeling and simulation” [Simul. Modell. Pract. Theory 42 (2014) 19–31]

http://dx.doi.org/10.1016/j.simpat.2014.05.004 1569-190X/ Elsevier B.V. All rights reserved. DOI of original article: http://dx.doi.org/10.1016/j.simpat.2013.12.005 ⇑ Corresponding author. Address: University of Ontario Institute of Technology (UOIT), Faculty of Energy Systems and Nuclear Science, 200 Street North, UOIT-FESNS 2000 Simcoe Street North, L1H7K4 ON, Canada. Tel.: +1 905 721 8668x5497; fax: +1 905 721 3046. E-mail addresses: aaabdelsalam@eng.suez.ed.eg (A.A. Abdelsalam), hossam.gabbar@uoit.ca, hossam.gaber@uoit.ca (H.A. Gabbar), farayi@q (F. Musharavati), shaligram@qu.edu.qa (S. Pokharel).