Combined Energy Analysis Research Articles

Numerical study of the energy loss in the bulb tubular pump system focusing on the off-design conditions based on combined energy analysis methods

The unsteady flow characteristics of the low-head bulb tubular pump highly affects the operation efficiency and stability of the whole system. The purpose of this paper is to investigate the dominating loss area in a typical tubular pump using the combined energy analysis methods. The transient multi-condition flow through the pump system is simulated based on N–S equation integrating SST k-ω model. The power loss characteristics of each flow passage component are analyzed in terms of total pressure variation, entropy production and energy balance equation. The turbulent entropy generation power (PSD') in the entropy production and the turbulent kinetic energy production (PL3) of the energy balance equation are the primary source of power loss, indicating that the fully developed turbulent flow tends to generate considerable loss in the pump system, followed by the power loss of solid wall (PSW and PLW). The distribution of power loss in the impeller and diffuser was comprehensively exhibited and it was found that the undesirable flow patterns are mainly caused by blades and walls. The rim region in impeller domain with volume fraction of 15% induces the energy loss of approximately 45% due to the presence of solid wall and tip leakage vortex (TLV). Furthermore, the individual grid volume is considered to better locate and visualize regions with our great interest, and a number of typical vortex structures are identified under several flow rates showing that the positive attack angle is more likely to caused flow instability and energy loss at low flow rate condition.

Indicative appraisal of clustered micro-generators for a low-carbon transition in the UK building sector

Building ‘zero carbon’ homes will be essential for achieving the carbon reductions within industrialised countries required to meet their commitments under the 2015 Paris Agreement on climate change. Such high performance buildings may need a combination or ‘cluster’ of micro-generators to be installed, such as a heat pump to provide heating and a solar photovoltaic (PV) array to produce electricity. When sized and installed appropriately, these technologies have lower emissions than the conventional systems they displace (centralised grid electricity and gas-fired boilers). However, if the ‘embodied’ energy and carbon is not recouped from that saved during the lifetime of the micro-generator, then there is no net saving overall. This study therefore assesses a range of clustered micro-generators using an ‘integrated approach’ that combines energy analysis, environmental life-cycle assessment, and an indicative financial appraisal. Eight clusters of micro-generators were designated to meet the heat and electricity requirements of five different dwelling types, each one specified to two different UK performance standards (2006 building regulations and a zero-carbon specification). For these 80 scenarios, various combinations of heat pumps with solar hot water and/or PV systems yield the most attractive performance metrics with all of the clusters having energy and carbon paybacks (4.5–5.5 and 5.0–7.0 years respectively) within their operational lifetimes, and would hence create net savings overall. But the clusters were generally found to have unattractive financial payback periods (50–80 years), although this result will be sensitive to the discount rate and prevailing energy prices and support mechanisms. The focus is on the use of clustered micro-generators in the context of UK transition pathways to a low-carbon economy out to 2050, but the lessons learned are applicable to many industrialised countries.

Compressor shaft work targeting using new numerical exergy problem table algorithm (ex-pta) in sub-ambient processes

One of the major challenges faced by energy intensive industries is an excessive greenhouse gas emission to the atmosphere due to high consumption of fossil fuels throughout the production processes. Due to high electricity usage in intensive industries, it is strongly advisable to all the engineers and other stakeholders to reduce the amount of energy needed for production, thus reducing carbon footprints. This is because the power generation industry emits approximately 37 % of total carbon dioxide emission to the atmosphere. Process improvement via Process Integration enhances the process energy efficiency, which contributes to the minimisation of fossil fuels and electricity consumption. Sub-ambient processes with refrigeration system are one of the highly energy intensive processes, which consumes a vast amount of electrical energy to run the compressors for fulfilling the process cooling demand. It is crucial to optimise the process-utility heat transfer in the system including the placement of compressors and expanders to minimise the exergy losses and shaft work consumption. This paper presents a combined energy analysis technique of Pinch Analysis and Exergy Analysis to determine exergy losses and compressor shaft work targeting in sub-ambient processes via a novel numerical approach known as the Exergy Problem Table Algorithm (Ex-PTA). The validity of the novel approach is demonstrated by using an illustrated case study. Based on the new numerical method, the total exergy loss in the process is 4.42 kW which is equivalent to 7.4 kW potential savings of compressor shaft work. In the economic analysis, the wasted potential shaft work costs a loss of approximately 19,926 MYR/y which should be avoided to minimise process operating cost.

Evaluation of low-impact modular housing using energy optimization and life cycle analysis

This paper presents life cycle analysis of the container-based single-family housing and combines energy analysis and optimization, life cycle assessment and life cycle costing. The proposed models include the container code (CC), designed to Canadian national building code as reference model, and an improved container (IC) incorporating passive solar technologies. Utilizing passive design strategies results in approximately 79% reduction in annual operational energy consumption for the improved case. The life cycle assessment considers the total energy use and global warming potential over 60-year lifespan. Three life cycle phases are considered: pre-use, use and operation, and end of life. As a result of envelope upgrade, the IC offers 77% reduction in life cycle energy use and global warming potential (GWP) than the CC. However, the envelope upgrade requiring greater energy intensity through industrial processing of additional building materials led to higher environmental impact, approximately 65,370 kWh of embodied energy and 20 t of CO2 eq of GWP embodied carbon emissions for the improved container at pre-use phase. In terms of life cycle cost, IC shows less than 10% total cost savings as compared to CC. This study, however, proves that integrating passive solar design techniques in building not only results in reduced energy consumption but rather translates to reduction in life cycle environmental impacts and life cycle cost building systems, which is, in this case, a modular container housing.

Life cycle assessment and life cycle costing of container-based single-family housing in Canada: A case study

This research presents an early-design analysis of single-family housing located in Calgary, Canada; and combines energy analysis, life cycle assessment (LCA), and life-cycle costing (LCC), to investigate the life cycle impacts associated with repurposing upcycled containers into modular housing. The study considers four case studies; container and lightwood designed to code specifications, both serving as base models and two improved models of container and lightwood, designed by incorporating energy efficiency measures and passive solar design standards.The life cycle assessment results for the code cases clearly show that majority of the life cycle environmental impacts (95%) occur at the use and operation phase, followed by the pre-use contributing 4%, and less than 1% at the end of life. For the improved cases, results show similar findings as the use and operation phase contributes approximately 85% impact, however, a higher pre-use impact of 12% is reported. Over the 50 years lifespan, the comparative life cycle impacts show only 3% difference when comparing container to lightwood cases.Sensitivity analysis show that utilizing Scenario 100:0 (container code-cut-of-method) in housing can result in a substantial amount of avoided impact about 46 (t CO2 eq) and (538 GJ) 149,444 kWh energy savings as compared to Scenario 0:100 (improved container – end of life recycling). Approximately 10% life cycle cost reduction is realized with the improved cases compared to code cases. This study proves the potentials for repurposing container for long-term usage as a building system, thereby meeting affordable housing needs with less environmental impacts.

The combined energy analyzer composed of electrostatic mirror fields

A model of an electrostatic spectrometer for the energy analysis of charged particles has been calculated. The instrument is based on a combination of hyperbolic and cylindrical mirrors. The scheme for an energy- and angle-resolved spectrometer which provides angular second-order focusing, high luminosity and exit angle 90° from the source has been theoretically substantiated.

Data-driven techniques to estimate parameters in the homogenized energy model for shape memory alloys

The homogenized energy model is a unified framework for modeling hysteresis in ferroelectric, ferromagnetic, and ferroelastic materials. The homogenized energy model framework combines energy analysis at the lattice level with stochastic homogenization techniques, based on the assumption that quantities such as interaction and coercive fields are manifestations of underlying densities, to construct macroscopic material models. In this article, we focus on the homogenized energy model for shape memory alloys. Specifically, we develop techniques for estimating model parameters based on attributes of measured data. Both the local (mesoscopic) and macroscopic models are described, and the model parameters’ relationship to the material’s response is discussed. Using these relationships, techniques for estimating model parameters are presented. The techniques are applied to constant-temperature stress–strain and resistance–strain data. These estimates are used in two manners. In one method, the estimates are considered fixed and only the homogenized energy model density functions are optimized. For SMA, the HEM incorporates densities for the interaction and relative stress (the width of the hysteresis loop). In the second method, the estimates are included in the optimization algorithm. Both cases are compared to experimental data at various temperatures, and the optimized model parameters are compared to the initial estimates.

Quantification of hysteresis and nonlinear effects on the frequency response of ferroelectricand ferromagnetic materials

Ferroelectric (e.g., PZT and PMN) and ferromagnetic (e.g., Terfenol-D) materials exhibithigh energy densities, broadband drive capabilities, and the capacity for both actuatingand sensing. This makes them attractive as compact transducers for a wide range ofapplications. However, the materials also exhibit hysteresis and constitutive nonlinearities,at all drive levels, that must be quantified and accommodated to achieve stringent trackingrequirements. Whereas considerable effort has been made on model development andunderstanding these materials in the parameter space and time domain, comprehensivequantification of these effects in the frequency domain is currently lacking. In this paper,we employ the homogenized energy model, in combination with thin beam theory,to quantify the frequency domain behavior of ferroelectric and ferromagneticmaterials. This model combines energy analysis at the lattice level with stochastichomogenization techniques to provide a framework that effectively quantifies theeffect of hysteresis, constitutive nonlinearities, bias fields and AC drive levels onthe material dynamics in both the time and frequency domains. Aspects of themodel are illustrated and validated through numerical and experimental examples.

Optimal Tracking Using Magnetostrictive Actuators Operating in Nonlinear and Hysteretic Regimes

AbstractMany active materials exhibit nonlinearities and hysteresis when driven at field levels necessary to meet stringent performance criteria in high performance applications. This often requires nonlinear control designs to effectively compensate for the nonlinear, hysteretic, field-coupled material behavior. In this paper, an optimal control design is developed to accurately track a reference signal using magnetostrictive transducers. The methodology can be directly extended to transducers employing piezoelectric materials or shape memory alloys due to the unified nature of the constitutive model employed in the control design. The constitutive model is based on a framework that combines energy analysis at lattice length scales with stochastic homogenization techniques to predict macroscopic material behavior. The constitutive model is incorporated into a finite element representation of the magnetostrictive transducer, which provides the framework for developing the finite-dimensional nonlinear control design. The control design includes an open loop nonlinear component computed off-line with perturbation feedback around the optimal state trajectory. Estimation of immeasurable states is achieved using a Kalman filter. It is shown that when operating in a highly nonlinear regime and as the frequency increases, significant performance enhancements are achieved relative to conventional proportional-integral control.

Experimental validation of a homogenized energy model for magnetic after-effects

In this letter, we experimentally validate the ability of a recently developed ferromagnetic hysteresis model to characterize magnetic after-effects in ferromagnetic materials. The modeling framework, which combines energy analysis at the lattice level with stochastic homogenization techniques to accommodate material, stress, and field nonhomogeneities, quantifies after-effects through a balance of the Gibbs and relative thermal energies. Attributes of the framework are illustrated through fits to experimental steel data.