Thermoelectric Plants Research Articles

Decommissioning of a fuel oil-fired thermoelectric power plant in Brazil - Economic feasibility under certain and risk conditions

The strategic analysis for the decommissioning of thermoelectric plants is seen as a trend for the coming years. The search for renewable alternatives should stimulate investment in other energy sources, reducing the number of thermoelectric plants in the energy generation system. However, few studies have dealt with the decommissioning of oil-fired thermoelectric plants. In this work, the methodology was applied under deterministic and stochastic conditions using methods of net present value (NPV), internal rate of return (IRR), discounted payback, capital asset pricing model (CAPM) and weighted average cost of capital (WACC). The results showed that the deterministic NPV was positive, ranging from R$101.30 million (pessimistic scenario) to R$109.73 million (optimistic scenario). The IRR was higher than the WACC of 10.55 %, ranging from 13.50 % to 13.68 % per year. For the Monte Carlo simulation, NPV was observed with 100 % certainty of viability and the probabilities of occurrence allowed more analysis of the risks involved than those obtained by deterministic methods. this study contributes to future decommissioning projects in Brazil, considering the scenario of stimulating renewable sources and the energy transition, helping managers make decisions about their projects. In addition, it helps guide public policies that can optimize the decommissioning process and strengthen the national energy sector.

Supply of bioelectricity from sugarcane bagasse in Brazil: a space–time analysis

Bioelectricity generation from sugarcane is significant across Brazil and is related to regional market structure characteristics where the mills are located. To understand the distribution and conjuncture of this sector, this study analyzes the pattern of location, concentration and clustering of the bioelectricity supply from sugarcane bagasse in Brazil, for 2017 and 2022. The data were obtained from the Brazilian National Electric Energy Agency, and the methodology was based on concentration indices and scan statistics. The results showed that the Southeast region presented the most thermoelectric power plants and installed capacity. The Southeast and Midwest regions were highly concentrated in terms of quantity and sugarcane bioelectricity installed capacity. Five clusters were identified for the number of power plants in 2017; for 2022, there were eight clusters. Regarding installed potential, there were 14 clusters in 2017 and 23 clusters in 2022, all statistically significant. The existence of clusters provides information on the competitive advantages in the national market, which can drive new investments in more densified areas or in the neighborhood. Identification of the location and concentration pattern showed that facilities in the state of São Paulo and the Northeast coast were responsible for the most important share of supply. These results indicate to investors the impact of electricity generation on the sector and the most relevant location for installing new thermoelectric plants.

Recognition of Intergranular Corrosion in AISI 304 Stainless Steel by Integrating a Multilayer Perceptron Artificial Neural Network and Metallographic Image Processing

The correct management of operations in thermoelectric plants is based on the continuous evaluation of the structural integrity of its components, among which there are elements made of stainless steel that perform water conduction functions at elevated temperatures. The working conditions generate progressive wear that must be monitored from the perspective of the microstructure of the material. When AISI 304 stainless steel is subjected to a temperature range between 450 and 850 °C, it is susceptible to intergranular corrosion. This phenomenon, known as sensitization, causes the material to lose strength and generates different patterns in its microstructure. This research analyzes three different patterns present in the microstructure of stainless steel, which manifest themselves through the following characteristics: the absence of intergranular corrosion, the presence of intergranular corrosion, and the precipitation of chromium carbides. This article shows the development of a methodology capable of recognizing the corrosion patterns generated in stainless steel with an accuracy of 98%, through the integration of a multilayer perceptron neural network and the following digital image processing methods: phase congruence and a gray-level co-occurrence matrix. In this way, an automatic procedure for the analysis of the intergranular corrosion present in AISI 304 stainless steel using artificial intelligence is proposed.

Analysis, Modeling, and Simulation Solution of Induced-Draft Fan Rotor with Excessive Vibration: A Case Study

In the modern industry, computer modeling and simulation tools have become fundamental to estimating the behavior of rotodynamic systems. These computational tools allow analyzing possible modifications as well as alternative solutions to changes in design, with the aim of improving performance. Nowadays, rotodynamic systems, present in various industrial applications, require greater efficiency and reliability. Although there are deep learning methodologies for monitoring and diagnosing failures which improve these standards, the main challenge is the lack of databases for learning, a problem that can be addressed through experimental monitoring and computer analysis. This work analyzes the vibrations of two induced-draft fans with excess vibration in a thermoelectric plant in Mexico. A vibration analysis was carried out through the instrumentation and monitoring of accelerometers located at crucial points in the fans. The results of this experimental analysis were validated by computer simulation based on FEM. The results show that the operating speed of the induced-draft fans is very close to their natural frequency, causing considerable stress and potential failures due to excessive vibration. Finally, this work presents a practical solution to modify the natural frequency of induced-draft fans, so that they can function correctly at the required operating speed, thus mitigating excessive vibration issues.

Decision support criteria for the implementation of waste-to-energy conversion systems: a case study in Southern Brazil

PurposeThe purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.Design/methodology/approachThe methodology is a simple case study with a qualitative approach. Five experts involved in the project of a thermoelectric power plant qualitatively evaluated, on a Likert scale, a decision model with 15 indicators derived from recent studies. The research object was the first stage of a project to implement a thermoelectric plant employing municipal solid waste (MSW) in southern Brazil.FindingsThe study identified 15 criteria supporting the decision-making process regarding WtE implementation for MSW in a mid-sized city in southern Brazil. The study identified that compliance with MSW legislation, compliance with energy legislation, initial investment and public health impact are the most influential criteria. The study offered two models for decision processes: a simplified one and a complete one, with ten and fifteen indicators, respectively.Research limitations/implicationsThe study concerns mid-sized municipalities in southern Brazil.Practical implicationsMunicipal public managers have now a methodology based on qualitative evaluation that admits multiple perspectives, such as technical, economic, environmental and social, to support decision-making processes on WtE technologies for MSW.Social implicationsMSW management initiatives can yield jobs and revenues for vulnerable populations and provide a correct destination for MSW, mainly in developing countries.Originality/valueThe main originality is that now municipal public decision-makers have a structured model based on four constructs (technical, economic, environmental and social) deployed in 15 indicators to support decision-making processes involving WtE and MSW management.

Typical solar extinction year at Plataforma Solar de Almería (Spain). Application to thermoelectric solar tower plants

The atmospheric extinction of solar radiation reflected by heliostats are recognized as an important factor of radiative losses in Concentrating Solar Power technologies in general and especially in thermoelectric solar tower plants. These types of plants are getting larger (≥100 MWe), and consequently the distances between the heliostats and the receiver very often exceed 1 km and radiative losses due to solar extinction on this path can represent a high percentage. The aerosols and water vapor along this route scatter and absorb solar radiation, preventing a percentage of it from reaching the solar receiver. For this reason, in the process of choosing a location for the design and construction of these plants, the radiative losses due to extinction in that place should be known in advance. Until now, Typical Meteorological Years have been available for the location chosen in the plant design stage, mainly considering Direct Normal Irradiance but not solar extinction. Unfortunately, ground-based measurement of solar extinction has never been properly considered because it was not known how to measure or estimate it adequately. The Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT, Spain) has developed a reliable solar extinction measurement system which has been recording accurate horizontal extinction values at Plataforma Solar de Almería (PSA) since 2017. Based on this unique in the world solar extinction database of more than five years, a Typical Solar Extinction Year has been obtained for the first time to rigorously validate extinction models that then allow knowing the extinction in any area of interest in the world for solar tower power plants and to choose the most convenient one. It has been found that the annual average extinction at PSA for the measurement distance (742 m) is 6 %, with a standard deviation of 2 % and a median of 6 %. This average annual extinction value corresponds to a horizontal extinction coefficient of (0.083 ± 0.029) km−1 and a Visual Range of 47 km (-12 km, +23 km). Frequent haze events have been observed at PSA mainly caused by Saharan dust, which can be considered one more symptom of the current increased desertification and climate change.

Just energy transition in Amazonia and the hydropower plants

The effects of climate change have been studied and publicized by experts, civil society movements and organizations, international organizations, and felt in different ways around the world. To combat climate change, an energy transition to renewable sources is necessary, in addition to other policies and measures, including combating deforestation and forest degradation. In the Amazon, the energy transition has driven the expansion of hydroelectricity, in some cases, such as in Brazil, the region being considered the new energy frontier. However, the energy transition cannot ignore social inequalities and environmental impacts, it needs to be just, leaving no one behind. And this challenge of a just transition that faces the Amazon region, a provider of hydroelectric energy, but with a large part of its population without access to energy, or with access to energy from thermoelectric plants. This article seeks to discuss the challenges of a just energy transition in the Amazon, taking into account the difficulty of accessing energy in the region and the expansion of hydroelectricity, with its socio-environmental impacts.

The Brazilian electricity system: an evaluation of the thermoelectric plants under the Eletrobras privatization law

As discussões sobre a transição energética (TE) no setor elétrico brasileiro (SEB) frequentemente consideraram a inserção de usinas termelétricas (UTEs) a gás natural (GN) como solução para a segurança energética. O SEB possui grande penetração de fontes renováveis (84%). A sua descarbonização é um mecanismo que pode contribuir para as metas brasileiras de redução das emissões de gases de efeito estufa (GEE) e ajudar a mitigar os impactos decorrentes das mudanças climáticas, a partir do aumento da participação das fontes renováveis. Nesse sentido, o objetivo do trabalho é analisar a exigência de contratação de 8.000 MW de novas UTEs a GN – térmicas-jabutis – a partir da Lei no 14.182/2021 de desestatização da Eletrobras e seu impacto no SEB. Metodologicamente, utilizam-se duas perguntas norteadoras: i) o SEB necessita de novas UTEs a GN?; e ii) quais os impactos da implantação das novas UTEs a GN previstas na lei de privatização da Eletrobras? Os resultados demonstram que a contratação compulsória de UTEs a GN no Brasil resultará em: i) custos adicionais de infraestrutura para transporte de GN até as UTEs; ii) aumento em 40% das emissões anuais de GEE do SEB; e iii) aumento da demanda por recursos hídricos, devido ao consumo de água para operação das UTEs. Por outro lado, para garantir o aumento da demanda de energia e a segurança energética do SEB no longo prazo, exige-se a expansão das redes de transmissão e da geração solar e eólica como meios mais econômicos para reduzir as emissões de GEE do setor elétrico. É preciso garantir a proteção da biodiversidade, os direitos das comunidades afetadas pela implantação desses projetos e a operação coordenada dessas novas usinas com o parque hidrelétrico brasileiro, de forma a garantir o armazenamento de energia na forma de água para períodos de escassez hídrica e para controle da carga. Por fim, conclui-se que: i) é fundamental considerar não apenas as emissões de GEE, mas também os impactos ambientais e sociais ao avaliar a expansão da geração de energia no Brasil; ii) a implantação das UTEs a GN é um contrassenso à TE brasileira, pois aumenta os impactos ambientais, o preço da tarifa de energia, retarda o atingimento das metas de descarbonização do SEB e da Agenda 2030; e iii) vai na contramão das evidências científicas, amplamente divulgadas nacionalmente e internacionalmente, que recomendam expandir a oferta brasileira de energia elétrica a partir de fontes solar e eólica. Portanto, o SEB não precisa de UTEs fósseis inflexíveis.

Efficiency Evaluation Of Filters Applied In Thermoeletrics From The Analysis Of Process Variables.

The generation of energy for thermoelectric has the benefit of not relying on environmental situations, as in the case of hydropower that can be influenced by the effects of weathering on the high or low level of its water reservoirs. However, the thermoelectric plants can bring harm to the environment by the emission of particulate material into the atmosphere. Filters of various principles can be used for containment of those fly ashes, as the cyclone filter. Given the relatively low costs involved this is widely used in a industrial scale and, for having a greater scope for gains in efficiency, will be addressed during this exposed. Is this article, it’s contemplated the study of the influence of the system’s variables, such as flow velocity of the gas inlet and the diameter of the particles suspended therein. It must be said that this study aims to technical study the filter, not normally considered the economic feasibility of possible changes and implementations; as such factors may serve as a disincentive to finding new methods and technology, which, since then, must be evaluated economically.

Uncertainty Evaluation of a Gas Turbine Model Based on a Nonlinear Autoregressive Exogenous Model and Monte Carlo Dropout.

Gas turbines are thermoelectric plants with various applications, such as large-scale electricity production, petrochemical industry, and steam generation. In order to optimize the operation of a gas turbine, it is necessary to develop system identification models that allow for the development of studies and analyses to increase the system's reliability. Current strategies for modeling complex and non-linear systems can be based on artificial intelligence techniques, using autoregressive neural networks of the NARX and LSTM type. In this context, this work aims to develop a model of a gas turbine capable of estimating the rotation speed of the turbine and simultaneously estimating the uncertainty associated with the estimation. These methodologies are based on artificial neural networks and the Monte Carlo dropout simulation method. The results were obtained from experimental data from a 215 MW gas turbine, getting the best model with a MAPE of 0.02% and an uncertainty associated with the turbine rotation speed of 2.2 RPM.

Contribution of the carbon tax, phase-out of thermoelectric power plants, and renewable energy subsidies for the decarbonization of Chile − A CGE model and microsimulations approach

There are various climate policies to decarbonize the energy matrix of a country. In the case of Chile, a carbon tax of 5 USD/tCO2 was initially implemented, and later, a schedule was established for the phase-out of coal-fired thermoelectric plants, all the above in the absence of subsidies for non-conventional renewable energy (NCRE). This study uses a computable general equilibrium (CGE) model and microsimulations to assess the contribution of current climate policies and other more demanding scenarios that accelerate the decarbonization of the Chilean energy matrix, considering economic, environmental, and distributional impacts. Specifically, carbon taxes are simulated with and without complementary climate policies (phase-out of coal-fired power plants and NCRE subsidies). The results show that the scenarios that combine the three climate policies generate a greater decrease in greenhouse gas emissions (40.4% ∼ 57.5%). Besides, the drop in GDP is more pronounced when coal-fired thermoelectric plants phase out (0.3% additional), and NCRE subsidies contribute to moderately reducing emissions. However, NCRE subsidies reduce the negative effect on households’ expenditure and income, especially in the poorest quintile. Finally, microsimulations show marginal changes in income distribution and an increase of up to 0.4 percentage points in the poverty rate.

Evaluation of Technical and Economic Indicators for the Production Process of Microalgae Lipids Considering CO2 Capture of a Thermoelectric Plant and Use of Piggery Wastewater

Microalgae are highly studied microorganisms for the production of high-value products due to their high content of proteins, lipids, carbohydrates, and chlorophyll. These compounds are refined to obtain profitable industrial products. This article analyzes the lipid production of Chlorella sp. biomass, considering 18 scenarios for its production, with 9 of these being partially supplemented with swine wastewater. A 1 ha area was considered for biomass cultivation, primary and secondary biomass harvesting, and lipid extraction. Using simulation in the software SuperPro Designer v10, parameters such as CO2 capture (from a thermoelectric power plant), freshwater consumption, wastewater consumption, energy consumption, and unit production cost were evaluated. The results show that the production cost is high, ranging from 836.9 US $/kg to 1131.5 US $/kg of produced lipids, with a maximum CO2 capture of 454 kg of CO2/kg of lipids. The use of wastewater reduces the production cost by approximately 10%. The evaluation of technical and economic parameters allows us to identify bottlenecks and implement strategies to reduce production costs.

Algorithm for Diffuse TSK Modeling of SNL MIMO with Undefined Operation Points

This paper presents an algorithm for constructing fuzzy models in linear state subspaces from the nonlinear MIMO dynamic model of plants whose operating points are not defined within the permissible physical range for the system. It is based on the fuzzy Takagi-Sugeno-Kang model and Kawamoto's ideas of non-linearity sectors. The relevant functions in the antecedent are modeled with linear functions, while functions model the consequent in Discrete State Space. The application of the algorithm to the model of a thermoelectric plant widely studied in the specialized literature is discussed.

Balancing cost, water, emissions, and reliability in power systems operations

Traditionally, large-scale thermoelectric power generation has been operated to reduce system operational costs. To expedite the mitigation of the harmful effects of climate change, many have proposed additional incentives for system operation (i.e. policies) that incorporate greenhouse gas emissions. However, such policies rarely consider unforeseen impacts on the volumes of water required for cooling thermoelectric plants as well as the potential effects on electricity production from water/climate-related stressors. We first create a case study representative of the thermoelectric-dominated water/energy systems in the Midwestern United States. Through this case study, our analysis investigates the tradeoffs of cost, water, emissions, and reliability in thermoelectric-dominated water/energy systems via policy analysis. Furthermore, we show how such policies respond differently to historic operational, climatological, and hydrological stressors. Specifically, we find that policies that focus on a single criterion can leave power systems vulnerable to reliability issues, operational cost increases, ecological impacts on riverine systems, and increased emissions. Therefore, consideration of many criteria (cost, water, emissions, and reliability) is necessary for creating an effective water-energy-emissions policy.

Circular economy strategy for the valorization of fly ash as a substitute for cement in monoliths (resistance and reactivity evaluation)

AbstractFly ash is currently a problem in different companies, mainly in thermoelectric plants, which must follow a production and consumption model that involves reusing, renewing, and recycling, thus contributing to the circular economy. This work aims to evaluate the reactivity and compressive strength of different types of ashes in concrete monoliths. For this purpose, sugarcane bagasse (SCBA), bituminous coal (BC), and untreated hazardous waste (RUD) were evaluated as replacements for cement. Monoliths and mortars have been manufactured in different mixtures, taken to a curing room, and their compressive strength and reactivity have been determined at different times (up to 28 days for the monoliths and up to 90 for the mortars), mainly in order to check the formation of calcium silicate hydrate (CSH) gels. In the monolith tests, the best performances have been with SCBA and BC, which have been used for the manufacture of the mortars. On day 56, the behavior of the replacement of 30% fly ash (15% BC:15% SCBA) presents a type H mortar behavior, with better results than the control. By day 90, all replacements had the same resistance as M mortars and even higher resistances than the control. This demonstrates the feasibility of its use in the production of Portland cement for the manufacture of low‐performance inputs. This implies the possible reduction of impacts, both in waste disposal sites and in emissions caused by the construction industry, thus contributing to the circular economy.

The current Brazilian energy model: 2016 to 2020

Power production growth in Brazil is a reality. Therefore, it is necessary carrying out analyses about energy sources to achieve sustainable and feasible development. A country with huge hydroelectric potential has the production of clean energy in comparison to other energy sources as positive feature. Observing the power generation sector’s origin, and comparing and understanding its dynamics, are duties of both the State and the community. The aim of the review in the present article is to objectively understand the Brazilian energetic potential and its several sources. Accordingly, a bibliographic review was conducted to better understand the Brazilian energetic scenario. Brazil accounts for the biggest biodiversity on the planet, as well as for having great climatic variety, such as equatorial, tropical and altitude tropical, sub-tropical, semiarid and Atlantic tropical climate. Brazilian power supply is in the hands of big power plants, like hydroelectric, thermo-electric, wind and solar plants. Hydroelectric plants correspond to approximately 59% of the country’s total installed capacity; moreover, it is often presented as clean and renewable energy source. Yet, although there is much to be developed when it comes to the sustainability of the hydroelectric source, it remains as the most feasible and cleanest Brazilian energy channel.

Numerical investigation of the influence of temperature and composition on the thermophysical properties of an innovative environmentally friendly glass obtained from mineral coal bottom ash

The purpose of this work is to investigate, through numerical simulation, the influence of temperature and chemical composition on the heat capacity, density, and thermal conductivity of a novel eco-friendly glass from mineral coal bottom ash. The modeling used to represent the system is based on the heat transfer in solids with phase-change. The numerical resolution was performed by the finite element method, and the variation of physical properties with temperature and composition was represented by theoretical and empirical equations introduced in the model. After the model is experimentally validated, the behavior of these properties during cooling process was investigated, pointing out higher ash content levels resulted in higher values of heat capacity, and lower values for density and thermal conductivity. Thus, this study brings contributions in the investigation of physical properties of a novel glass obtained by reuse of mineral coal bottom ash from a thermoelectric plant.

Synergistic cotreatment of cooling tower blowdown and produced waters: Modeling strategies for a comprehensive wastewater treatment simulation

Cooling tower blowdown from thermoelectric power plants and produced water from hydraulic fracturing may soften when mixed due to the complimentary chemistry of the two wastewaters. The potential benefit of low effort softening warrants the investigation of a cotreatment process concerning these industrial wastewaters. The synergy is expected to lessen chemical demand for softening and further enable sustainable practices such as designing for a zero-liquid discharge (ZLD) process. The treatment process may then provide a treated effluent suitable for use as blowdown makeup. In this study, the feasibility and effectiveness of a cotreatment train is explored through simulation of chemical softening, filtration, reverse osmosis (RO), multi-effect distillation (MED), and electrolysis unit operations within a comprehensive process model. Innovative modeling strategies are necessary to result in a meaningful process model when considering the significant complexity of the water chemistry for this treatment train. Through the methodology described in this work, a feasible process design is presented as a base case for treatment of experimentally characterized blowdown and produced water samples obtained in the northern Appalachian region. Thereafter, the base case also establishes a platform for more detailed process analyses of different scenarios in future work. Detailed descriptions of modeling methodologies, process design decisions, and simulation results are provided as a perspective on comprehensive modeling of multi-technology treatment trains for complex feedwaters. With the results of the cotreatment simulation, it is determined that the total water recovery of the process may serve to completely makeup the blowdown rate and partially make up the evaporative losses of a theoretical thermoelectric plant's water demand. This complete recovery is evaluated to require 18,343.531 kW of a chemical energy equivalent, 1184.971 kW of electricity, and 68,126.291MJh−1 of power plant steam to result in 408.532m3h−1 of treated water effluent at a quality of approximately 0.135gL−1 total dissolved solids for the base case design.

Towards renewable energy projects under sustainable watersheds principles for forest biomass supply

The transition in the global energy matrix to sources of renewable electric generation has been the main demand of countries in the face of a state of climatic emergency. Forest biomass is a potential alternative to meet the growing demand. The expansion of thermoelectric projects based on forest residues highlights the need to assess raw materials' availability and land suitability. This is usually a problem of spatial decision and geographic intelligence under a holistic perspective since, in planning these projects, it is essential to understand the economic, environmental, and social feasibility. In this article, we propose a decision support system based on multi-criteria modeling on a GIS structure associated with a mathematical optimization model for zoning the suitability and availability of land for constructing thermoelectric power plants. The geospatial model for determining priority sites integrated various environmental, social, and economic criteria and constraints. The AHP method was used to weigh and estimate the relative importance weights of the criteria for modeling territorial aptitude. The results of the GIS stage formed the basis of a mixed-integer linear programming model that incorporated technical and economic aspects for a better allocation of financial resources. The minimized cost function included transport costs, harvesting, forestry, purchasing land/leasing land/forest outgrower schemes, and purchasing wood from the market to supply the biomass. We used a sizeable hydrographic basin in southeastern Brazil as a case study for the demonstration. The mapping of suitability and constrained zones identified the classes of preference and availability of land. The proposed mathematical model recognized sets of supply locations (new plantations or existing areas) and minimized the project's final cost to supply biomass to meet the demand of potential thermoelectric plants that are candidates for implementation. Despite the problem's large scale and the large data set, our findings indicated that we could provide a broad and multidimensional view of the potential of developing electrical generation systems based on forest biomass. The methodology and the model proposed in this study can be replicated in other global regions and modified to assess other resources from different biomasses and bioenergy systems. Our study promotes the UN's sustainable development goals, particularly SDG 7 (Affordable and clean energy) and SDG 13 (Climate Action).

Enhancing composite materials through fly ash reinforcement through powder metallurgy

The utilization of fly ash as reinforcement in composites offers a cost-effective alternative for applications involving ductile metallic matrices. Ash is a by-product of coal combustion in thermoelectric plants, and its use can serve as an environmentally friendly option. Fly ash exhibits characteristics of a ceramic material. However, there are gaps in understanding the mechanical and metallurgical behavior resulting from the interaction between the matrix and the fly ash-based reinforcement. This study aims to develop and evaluate the application of various amounts of fly ash as reinforcement in metal matrix composites through the powder metallurgy process. The process adheres to internationally recognized standards for incorporating ashes into metallic composites. The method involved producing specimens with no fly ash (0FA) and using 5%, 10%, and 15% fly ash (5FA, 10FA, 15FA). The samples were assessed for density, microstructure, microhardness, and wear coefficient using established techniques. Through graphical and statistical analyses, the research examined the impact of reinforcements on the metallic matrix. The results indicate that including fly ash as a composite reinforcement led to a reduction in density with a variance level of F′ 17.7. The microhardness values were not significantly affected, with F′ 0.46. There was a noticeable improvement in wear resistance for 200 cycles (F′ 22.7), 400 cycles (F′ 4.7), and 600 cycles (F’ 0.58). In conclusion, employing composites reinforced with fly ash of varying compositions is feasible, using highly applied compressive pressures and the powder metallurgy process.