Compression Costs Research Articles

Optimization of a Typical Gas Injection Pressurization Process in Underground Gas Storage

In the early construction of an underground gas storage facility in an oil and gas field in southwest China, the increasing gas injection volume led to a continuous rise in energy consumption, which affects the economic sustainability of gas injection and extraction. In order to improve efficiency and reduce energy consumption, optimization of the pressurization process was carried out. An optimization model for the process of pressurization in underground gas storage has been established. Based on the model, a joint optimization approach is applied, where MATLAB is responsible for the iterative process of finding the optimal parameter combinations and HYSYS is responsible for the establishment of the process and calculation of the results of the process parameters. The key parameters include the outlet parameters of the compressor and the air cooler, which are critical in determining the overall energy consumption and operational performance of the system. Accordingly, the results related to the optimal parameter combinations for two-stage compression and three-stage compression were obtained in the case study. Compared with one-stage compression, two-stage and three-stage compression can diminish energy consumption by 1,464,789 kJ/h and 2,177,319 kJ/h, respectively. The reduced rate of energy consumption of three-stage compression was 16.10%, which was higher than that of two-stage compression by 10.83%. Although the construction costs of three-stage compression were higher than those of two-stage compression, from the perspective of long-term operation, three-stage compression had lower operating costs and superior economy and applicable value. The research results provided scientific references and new ideas for the optimization and adjustment of the pressurization process in underground gas storage.

Techno-Economic Feasibility Analysis of Post-Combustion Carbon Capture in an NGCC Power Plant in Uzbekistan

As natural gas-fired combined cycle (NGCC) power plants continue to constitute a crucial part of the global energy landscape, their carbon dioxide (CO2) emissions pose a significant challenge to climate goals. This paper evaluates the feasibility of implementing post-combustion carbon capture, storage, and utilization (CCSU) technologies in NGCC power plants for end-of-pipe decarbonization in Uzbekistan. This study simulates and models a 450 MW NGCC power plant block, a first-generation, technically proven solvent—MEA-based CO2 absorption plant—and CO2 compression and pipeline transportation to nearby oil reservoirs to evaluate the technical, economic, and environmental aspects of CCSU integration. Parametric sensitivity analysis is employed to minimize energy consumption in the regeneration process. The economic analysis evaluates the levelized cost of electricity (LCOE) on the basis of capital expenses (CAPEX) and operational expenses (OPEX). The results indicate that CCSU integration can significantly reduce CO2 emissions by more than 1.05 million tonnes annually at a 90% capture rate, although it impacts plant efficiency, which decreases from 55.8% to 46.8% because of the significant amount of low-pressure steam extraction for solvent regeneration at 3.97 GJ/tonne CO2 and multi-stage CO2 compression for pipeline transportation and subsequent storage. Moreover, the CO2 capture, compression, and transportation costs are almost 61 USD per tonne, with an equivalent LCOE increase of approximately 45% from the base case. This paper concludes that while CCSU integration offers a promising path for the decarbonization of NGCC plants in Uzbekistan in the near- and mid-term, its implementation requires massive investments due to the large scale of these plants.

Hybrid extreme gradient boosting regressor models for the multi-objective mixture design optimization of cementitious mixtures incorporating mine tailings as fine aggregates

The design of cementitious mixtures incorporating mine tailings as fine aggregates is a multi-objective optimization (MOO) problem, in which both the uniaxial compressive strength (UCS) and cost of the mixtures need to be considered simultaneously. Given that data-driven methods have shown promising results when solving similar MOO problems, this study developed an extreme gradient boosting regressor (XGBR) model on a dataset extracted from the literature to predict the UCS. Among the efforts taken to improve the models, a genetic algorithm (GA)-based XGBR model demonstrated the optimal prediction performance, with an R2 of 0.959. Next, the GA-XGBR model and a cost equation were used as objective functions in the MOO problem. The non-dominated sorting genetic algorithm with elite strategy (NSGA-II) was selected to solve the optimization problem. A case study was conducted, generating mixture designs that offered improved trade-offs between cost and UCS compared to experimental designs. Finally, a graphical user interface was developed to provide access to the prediction model and optimization method. Overall, this work can be used as a guide for optimal mixture designs as it facilitates informed decision-making before the actual applications.

Reverse design for mixture proportions of recycled brick aggregate concrete using machine learning-based meta-heuristic algorithm: A multi-objective driven study

Construction and Demolition Wastes (CDW) have a significant impact on global waste streams. Brick waste stands out as a prominent type of CDW, and numerous studies have explored its recycling for the creation of environmentally-friendly concrete. Reverse design of recycled brick aggregate concrete (RBAC) mixture proportion is presented in this paper with a focus on four key objectives, that is: compressive strength, cost, and environmental elements (i.e., energy consumption and carbon emission). Based on compiled experimental datasets of 374 samples, the back propagation neural network (BP), random forest (RF), and four meta-heuristic algorithm optimization models were constructed to achieve the desired compressive strength objective. In all machine learning (ML) methods, the compressive strength of RBAC can be predicted with high accuracy, with the SSA-BP (optimized back propagation neural network model using the sparrow search algorithm) model achieving superior results (i.e., NSE=0.91, RPD=3.2). The SSA-BP is therefore used as the objective function for compressive strength. The economic objective is primarily influenced by material costs, and the objective functions of energy consumption and carbon emission are determined by various aspects of production, transportation, and their mixing processes. In order to obtain the optimal RBAC design, the Non-Dominated Sorting Genetic Algorithm (NSGA-III) was implemented considering imperative constraints. Results indicate that cement amount and recycled brick aggregate (RBA)-to-natural aggregate proportion have a positive impact on the compressive strength. The suggested design framework allows for the creation of RBAC composite designs with varying levels of RBA substitution rates and strength targets, providing valuable guidance for tackling the CDW challenge and optimizing RBA usage.

Sustainable and mechanical properties of Engineered Cementitious Composites with biochar: Integrating Micro- and Macro-Mechanical Insight

Engineered Cementitious Composites (ECC) are ductile, strain-hardening cementitious composites with a tightly controlled crack opening profile. A significant concern in the development and application of ECC is its high carbon emissions associated with high cement content consumption. As an emerging green additive, biochar can significantly cut down on the carbon emission of concrete products. However, research that integrates micro- and macro-mechanical insights with biochar incorporation is limited. In this study, micro-mechanical tools indicated that a certain amount of substitution biochar could enhance the tensile properties of ECC. The study assessed various properties including compressive strength, porosity, density, tensile performance, crack pattern, sustainability and cost of ECC with different biochar proportions. The findings showed that incorporating 10% to 20% biochar effectively increased the tensile strain capacity and decreased the crack opening width in ECC materials. This improvement can be attributed to the introduction of finer biochar particles (≤75μm) at the fiber/matrix interfacial transition zone, which alters the fiber-bridging force by reducing the chemical and frictional bond strength between the fiber and matrix, as revealed by micro-mechanical tests and microstructural inspection. Moreover, the utilization of biochar contributes to reducing the carbon emission of ECC, enhancing sustainability while maintaining a ∼10% minimal reduction in compressive strength. Overall, this study introduces a novel approach for reusing low-carbon biomass waste in the production of building materials, offering potential advantages in micro- and macro-mechanical performance, cost-effectiveness, and environmental sustainability.

Process-integrated optimization and techno-economic analysis of membrane system for biogas upgrading: Effect of membrane performance from an economic perspective

It is useful to be able to predict the potential economic performance of new membrane materials and the associated configurations of equipment which would give the best possible performance with these materials. In this study we propose a systematic search of ranges of different possible membrane properties. The properties varied here include the CO2 permeance and the CO2/CH4 selectivity, and a 2D grid with different values of each property is investigated. For each individual combination of properties a superstructure optimization is used to find the configuration and operating pressures which minimize the cost of biogas upgrading. Applying this to every point in the grid gives a surface of upgrading costs across the ranges of possible CO2 permeances and selectivities. Subsequently a correlation equation is fitted to this data which can be used to predict the potential economic performance of future possible materials within this range. In general the upgrading costs reduce when either of these parameters are increased but for different reasons. Higher permeances allow smaller area of membranes to be used allowing lower membrane costs while higher selectivities reduce the need for recycling and associated compression costs. The selectivity, in particular, is found to strongly affect the optimal configuration with high selectivities allowing for designs without recycling while lower selectivities force the process to include recycling streams in order to meet recovery and purity targets. It is expected that the proposed correlation could be used to quickly evaluate the economic performance of new materials as they are being developed and tested.

Optimized Design of Low-Carbon Mix Ratio for Non-Dominated Sorting Genetic Algorithm II Concrete Based on Genetic Algorithm-Improved Back Propagation.

In order to achieve low-carbon optimization in the intelligent mix ratio design of concrete materials, this work first constructs a concrete mix ratio database and performs a statistical characteristics analysis. Secondly, it employs a standard back propagation (BP) and a genetic algorithm-improved BP (GA-BP) to predict the concrete mix ratio. The NSGA-II algorithm is then used to optimize the mix ratio. Finally, the method's accuracy is validated through experiments. The study's results indicate that the statistical characteristics of the concrete mix ratio data show a wide distribution range and good representativeness. Compared to the standard BP, the fitting accuracies of each GA-BP set are improved by 4.9%, 0.3%, 16.7%, and 4.6%, respectively. According to the Fast Non-Dominated Sorting Genetic Algorithm II (NSGA-II) optimization for meeting C50 concrete strength requirements, the optimal concrete mix ratio is as follows: cement 331.3 kg/m3, sand 639.4 kg/m3, stone 1039 kg/m3, fly ash 56 kg/m3, water 153 kg/m3, and water-reducing agent 0.632 kg/m3. The 28-day compressive strength, material cost, and carbon emissions show relative errors of 2.1%, 0.6%, and 2.9%, respectively. Compared with commercial concrete of the same strength grade, costs and carbon emissions are reduced by 7.2% and 15.9%, respectively. The methodology used in this study not only significantly improves the accuracy of concrete design but also considers the carbon emissions involved in the concrete preparation process, reflecting the strength, economic, and environmental impacts of material design. Practitioners are encouraged to explore integrated low-carbon research that spans from material selection to structural optimization.

Research on the Application of New Energy and Low-carbon Technologies in the Repair of Concrete Surface Defects

Photovoltaic heating is a new energy technology, which plays an obvious role in concrete curing, which can shorten the curing time of concrete. However, the role of this technology in concrete surface repair is not clear. In order to expand the application scope of low-carbon energy, this paper takes concrete surface repair as the research object and conducts photovoltaic heating analysis. Firstly, the data of concrete surface depression were collected, and then the repair effect of photovoltaic heating technology on the concrete surface was analyzed with C30 # as the research object, such as compressive strength, curing time, complex spacing, repair cost and energy consumption. and analyze the range of variation of each indicator; The results show that the photovoltaic heating technology can shorten the curing time by 20% and improve the compressive strength to 50kg/m2 with a complex spacing of less than 20 microns. At the same time, the repair cost and energy consumption are reduced, and the reduction range is 15~18%. Therefore, new energy and low-carbon technologies such as photovoltaic heating can effectively repair concrete surface defects, build on the cost and energy consumption of repair, improve the repair time, and meet the overall requirements of concrete construction.

Multi-objective optimization design of a circular core paper sandwich panel

Abstract Ensuring sufficient mechanical performance while enabling lightweight design is critical for utilizing paper sandwich panels in the furniture industry. To design lightweight sandwich panels that balance mechanical properties and cost, this study developed a circular core paper sandwich panel (CCPSP) and investigated its structural efficiency using multi-objective optimization. The response surface method (RSM) based on Box–Behnken design was utilized to establish mathematical models relating the paper tube spacing, inner diameter, and height to the out-of-plane compressive strength, density, and cost. The resulting models effectively revealed the coupled effects of the parameters on the responses. Subsequently, the models were optimized using the non-dominated sorting genetic algorithm II (NSGA-II) to find the Pareto optimal trade-offs between maximizing compressive strength while minimizing its density and cost. The optimization solution resulted in an optimal set of paper tube geometries that maximized the structural efficiency of CCPSP. Overall, lower tube height conferred superior structural efficiency, while tube spacing and diameter were constrained. The results highlight the potential of CCPSP as an efficient and sustainable material for furniture manufacturing, enabled by multi-objective optimization of its structure.

Investigation of the Mechanical Behaviors of Sustainable Green Reactive Powder Concrete Produced Using Ferrochrome Slag and Waste Fiber

Reactive powder concrete (RPC) is a new generation concrete with high strength, used in special structures, and its use is increasing day by day. In this study, instead of using high-strength aggregates typically used in RPC, wastes released in ferrochrome production were used. In addition, the possibility of using fibers obtained from end-of-life automobile tires (ELT), instead of the micro steel fibers typically used in RPC, was investigated. Thus, sustainable green reactive powder concrete (GRPC), the material which is obtained from waste materials except the binder and chemical additive, has been developed. As ferrochrome wastes, olivine, serpentine, rum, slag, and pure waste were used as powder and aggregate in GRPC. Firstly, in GRPC without fiber, the physical and mechanical properties of ferrochrome wastes were examined by using different ratios. Then, the optimum mixture was selected, and different ratios of industrial steel and ELT fiber were added to this mixture. As a result, the compressive strength of GRPC using olivine and pure waste (ferrochrome slag) is close to the reference RPC. However, it is 28% more economical. The flexural strength of the samples with a 4% addition of industrial or ELT fiber increased by 182% and 213%, respectively, compared to the reference sample without fiber. With the use of 4% ELT fiber (by volume) in GRPC, the flexural strength increased by 11% compared to the use of industrial steel fiber. In terms of cost, with the use of ferrochrome waste and ELT fiber, GRPC was 48% more economical. When examined in terms of the flexural and compressive unit strength cost, GRPC was approximately 41% more economical. As a result of this study, high-performance concrete with high mechanical properties that is economical, sustainable, and environmentally friendly has been produced by evaluating the use of waste materials.

Maximizing Production Profits: Optimizing Gas Lift Design in the Halfaya Oil Field

Gas lift is one of the most common artificial lift methods which is effectively utilized in the oil industry for enhancing production. However, proper gas allocation into wells can be challenging due to various limitations such as shortage in injected gas and economic considerations. Therefore, the current research is conducted to address the critical requirement to effectively distribute gas to maximize profits in the Halfaya Oil Field- Mishrif formation. Continuous gas lift is one of the most commonly used artificial lift methods. To enhance production rate, a sufficient amount of gas is injected into the production tubing at specific depths to reduce the liquid column pressure as each well has an optimal point for production in an oil reservoir. On the other hand, constraints of gas availability restrict achieving the optimal state of production. Such restrictions combined with economic limitations including high gas prices and compression costs, emphasized the necessity for optimal methodology to enhance oil production. Aside from the importance of the Halfaya oil field, there are limited relevant studies on artificial lifting methods specifically associated with the gas-lifting method used in this paper. Thus, the purpose of the current investigation is to propose a well-tested gas lifting design for oil production improvement. The approach combines the skill of the fmincon function built in MATLAB as an optimizer and the PIPESIM network model to create gas lift performance curves. This resulted in an oil production rate of 18860 STB/d, with a gas lift rate of 9.42 mmscf/d. Establishing such a systematic optimization process can manage the challenges of gas allocation in the Halfaya Oil Field towards maximizing production rates and ultimately increasing net profits.

Пошук оптимальних складів фібробетонів жорсткого дорожнього покриття з використанням експериментально-статистичних моделей

The experiment was conducted according to a 15-point plan. In the experiment, the following three factors of the composition of rigid pavement fiber-reinforced concrete varied: the amount of Portland cement from 290 to 350 kg/m3, the amount of basaltic fiber from 0.9 to 1.5 kg/m3, the amount of superplasticizer from 0.6 to 1% of the cement mass. A set of experimental statistical models was obtained. They describe the influence of factors on compressive strength, flexural strength, frost resistance, abrasion resistance and cost of fiber-reinforced concrete. The selection of optimal compositions of fiber-reinforced concrete rigid pavement for the roads of II-III and Ib categories was carried out using these models. The selection of optimal compositions of fiber-reinforced concrete was carried out graphically using square diagrams. The method of representing the factor space as 7 "square" type diagrams was used when fixing the amount of cement in the composition from 290 to 350 kg/m3 with a step of 10 kg/m3. This discretization allows for a clearer and more accurate search for optimal solutions. The levels of compressive strength, flexural strength and frost resistance were used as limitation criteria. These levels meet the requirements of DBN B.2.3-4:2015 for rigid pavement materials of the corresponding category. The concrete cost index was used as an optimization criterion. The abrasion resistance of concrete was also controlled to guarantee a correct choice. Two compositions of fiber-reinforced concrete for the roads of the II and III categories were chosen. These compositions have a compressive strength of 43 and 45 MPa, a flexural strength of 5 and 5.1 MPa, abrasion of about 0.36 g/cm2 and frost resistance of F200. Two compositions of fiber-reinforced concrete for category Ib roads were also selected. These compositions have a compressive strength of 48 and 50 MPa, a flexural strength of 5.5 MPa, abrasion of about 0.35 g/cm2 and frost resistance of F200. The compositions have chosen the lowest cost price while ensuring the strength and durability of the material. The use of this fiber-reinforced concrete makes it possible to increase the intervals between repairs during the maintenance of cement concrete roads in typical climatic conditions in Ukraine.

Influence of the composition of alkali-activated lime-metakaolin mortars on compressive strength, cost, and CO2 emission

The environmental impact associated with Portland cement production makes it necessary to explore alternatives that minimize the polluting effects of this industrial activity. A promising approach is the development of alkali-activated mortars composed of lime and pozzolan. Therefore, the objective of this study was to analyze the influence of components on the compressive strength of alkali-activated lime-metakaolin mortars. The mortar composition was defined in three ways: the first way followed the guidelines of the Brazilian standard NBR 5751 and used the specific masses of the materials; the second was based on the CaO/SiO2 mass ratio, analyzing the reasons for 0.40 and 0.75 and the third followed the guidelines of NBR 7215 standard and ratio of 0.75. In this last composition, the alkaline activator (NaOH) was incorporated in proportions of 1.5%, 3%, 4.5%, and 6%. The results indicated that the lime: metakaolin ratio has a significant impact on strength, with a 34% decrease in compressive strength when the lime-pozzolan ratio was reduced from 3.35 to 1.77. Furthermore, it was observed that the addition of an alkaline activator improved mechanical resistance. Therefore, these mortars proved to be viable for several non-structural applications, highlighting their environmental advantages in comparison with Portland cement mortars.

On Nonlinear Compression Costs: When Shannon Meets Rényi

On Nonlinear Compression Costs: When Shannon Meets Rényi

Development of Non-Load Bearing Three-Core Stretcher Concrete Masonry Unit With Polyethylene Terephthalate Waste

Persistent problems stem from factors such as the difficulty of waste recycling wherein plastics are substantial contributors having strong environmental impact. To mitigate this dilemma, reengineered plastics are emerging as reforms in solving solid waste management issues. This study aimed to investigate the effects of utilizing Polyethylene terephthalate (PET) as an admixture in a non-load-bearing concrete masonry unit. Moreover, it sought to limit the amount of environmental degradation and prevent ecological and environmental strains caused by plastic. This study used the experimental method which involved compressive strength testing, unit weight, and unit cost analysis. In addition to this, the properties of the materials were studied to arrive at the optimum percent composition to generate the highest efficiency. Five treatments were utilized including the control (0%), 1.5%, 2.0%, 2.5%, and 3.0% PET waste admixture. In the findings, both the control CMU and the 1.5% PET waste admixture have qualified on the standard specification, ASTM C129, for CMU compressive strength. The unit weight decreases as the amount of admixture increases. In terms of unit cost, the sample with the highest percentage of PET waste has the lowest unit cost but with the lowest compressive strength. However, between the control CMU and the 1.5% PET waste admixture, the latter has a lower unit cost. Therefore, it can be inferred that adapting the use of PET wastes as admixture at 1.5% showed the most competence proving to reduce plastic waste environmental issues while gaining higher possible profit when introduced into the commercial industry of construction supplies. For future studies, a Comparative Analysis of walls made with plain and PET waste concrete masonry units may be conducted to improve the application of the material.

Importance of Bridging Molecular and Process Modeling to Design Optimal Adsorbents for Large-Scale CO2 Capture.

ConspectusCarbon capture, utilization, and storage have been identified as key technologies to decarbonize the energy and industrial sectors. Although postcombustion CO2 capture by absorption in aqueous amines is a mature technology, the required high regeneration energy, losses due to degradation and evaporation, and corrosion carry a high economic cost, precluding this technology to be used today at the scale required to mitigate climate change. Solid adsorbent-based systems with high CO2 capacities, high selectivity, and lower regeneration energy are becoming an attractive alternative for this purpose. Conscious of this opportunity, the search for optimal adsorbents for the capture of CO2 has become an urgent task. To accurately assess the performance of CO2 separation by adsorption at the needed scale, adsorbents should be synthesized and fully characterized under the required operating conditions, and the proper design and simulation of the process should be implemented along with techno-economic and environmental assessments. Several works have examined pure CO2 single-component adsorption or binary mixtures of CO2 with nitrogen for different families of adsorbents, primarily addressing their CO2 adsorption capacity and selectivity; however, very limited data is available under other conditions and/or with impurities, mainly due to the intensive experimental (modeling) efforts required for the large number of adsorbents to be studied, posing a challenge for their assessment under the needed conditions. In this regard, molecular simulations can be employed in synergy with experiments, reliably generating missing adsorption properties of mixtures while providing understanding at the molecular level of the mechanism of the adsorption process.This Account provides an outlook on strategies used for the rational design of materials for CO2 capture from different sources from the understanding of the adsorption mechanism at the molecular level. We illustrate with practical examples from our work and others' work how molecular simulations can be reliably used to link the molecular knowledge of novel adsorbents for which limited data exist for CO2 capture adsorption processes. Molecular simulation results of different adsorbents, including MOFs, zeolites, and carbon-based and silica-based materials, are discussed, focusing on understanding the role of physical and chemical adsorption obtained from simulations and quantifying the impact of impurities in the performance of the materials. Furthermore, simulation results can be used for screening adsorbents from basic key performance indicators, such as cycling the working capacity, selectivity, and energy requirement, or for feeding detailed dynamic models to assess their performance in swing adsorption processes on the industrial scale, additionally including monetized performance indicators such as operating expenses, equipment sizes, and compression cost. Moreover, we highlight the role of molecular simulations in guiding strategies for improving the performance of these materials by functionalization with amines or creating hybrid solid materials. We show how integrating models at different scales provides a robust and reliable assessment of the performance of the adsorbent materials under the required industrial conditions, rationally guiding the search for best performers. Trends in additional computational resources that can be used, including machine learning, and perspectives on practical requirements for leveraging CO2 capture adsorption technologies on the needed scale are also discussed.

Microgrids for green hydrogen production for fuel cell buses – A techno-economic analysis for Fiji

The study examines the feasibility of producing hydrogen for fuel cell buses in Fiji. The paper focuses on sizing hybrid microgrids comprising solar panels and wind turbines as the primary power source for hydrogen production while considering both off-grid and grid-connected cases. As no fuel cell vehicles exist in Fiji at present, five long-distance buses with daily travel of 380 km are proposed as a pilot scale baseline system, which would operate in the daytime only. Detailed technical and economic modelling was done using the HOMER Pro software with cost inputs derived from literature. A total of three cases for the on-grid and four cases for the off-grid systems are analyzed based on the various combinations of components. HOMER Pro optimized the grid configurations to minimize the Net Present Cost (NPC) values. All seven cases were also modelled with and without the effects of hydrogen gas compressors to emulate the production of low-pressure gas without compression and compressed high-pressure hydrogen required for fuel cell buses. It was found that a grid-connected system with solar and wind hybrid was the most feasible configuration and yielded the lowest NPC of $6 million. The grid-connected case also yielded a Levelized Cost of Electricity (LCOE) of $0.10/kWh and a Levelized Cost of Hydrogen (LCOH) of $9.08/kg with compression to 400 bars. The LCOH stood at $8.73/kg for hydrogen generation without compression. The most feasible off-grid configuration using solar and wind power attained an LCOE of $1.15/kWh while giving a LCOH of $13.00/kg for compressed hydrogen. It was also found that neglecting hydrogen compression load and costs can underestimate the LCOH by as much as 6.92 %. The off-grid best case had no CO2 produced during its operation, leading to a net zero process that offsets 929.9 tons of CO2 compared to the baseline. The grid-connected system does have some emissions but leads to a 93.9 % reduction in CO2 emissions, offsetting 873.3 tons of CO2 compared to the baseline. The study updated the cost inputs to account for inflation, logistics, and hydrogen gas compression, which are not available directly in HOMER Pro software. At the time of writing this paper, no feasibility study existed for hydrogen production in Fiji using renewable energy.

Optimization of additives in cement mortar using Taguchi method

Recent emerging developments in construction works have introduced many enormous and wonderful construction materials. But till now, cement based construction materials are being used in various activities e.g., masonry, lining, grouting etc. Cement, a key ingredient for various construction materials, needs to be replaced by another natural or artificial inert, due to its perilous effects in ecology. The present study has been conducted to evaluate the compressive strength, electrical resistivity, cost analysis and environment assessment of cement mortar after replacing the cement with various proportions of Kota stone powder. Calcium nitrate and triethanolamine were also added to the mortar mixes to control the parametric behaviours of the mixes. The Taguchi technique has been used to curtail the number of mix proportions for effort saving practices. Taguchi technique produces a data set of lesser experimental runs than a full factorial approach. Therefore, Taguchi method could be used to optimize the number of combinations to make the project cost-effective. The purpose of this study is to evaluate the performance of cement mortar containing calcium nitrate, triethanolamine, and Kota stone powder in various proportions with respect to various attributes. An L9 (3^3) orthogonal array containing nine mortar blends was analyzed to optimize the process parameters on the basis of the laboratory responses. Results of the study positively affirmed that the efficacy of the incorporation of Kota stone powder in mortar has yielded as economic and ecological construction material over other additives.

Exploration of the effects of electrolytic manganese residue on the environmental, economic, and engineering performance of magnesium oxychloride cement: A possible utilization method of electrolytic manganese residue

The widespread use of magnesium oxychloride cement (MOC) can effectively solve the waste problem in the potash industry. However, its poor water resistance limits its practical application. Electrolytic Manganese Residue (EMR), as a solid waste from manganese metal smelting, requires an effective utilization method. In this work, we have attempted to incorporate EMR into MOC after its treatment in order to improve the water resistance of MOC and increase the utilization rate of EMR. The addition of EMR to MOC increased the density of MOC. The incorporation of EMR did not significantly reduce the strength of the MOC samples. The incorporation of EMR reduced the relative content of magnesium oxide in the specimens and EMR can be used as a source of soluble Al, Si and Fe to produce insoluble amorphous gels. The combined effect resulted in an effective improvement in the water resistance of the samples. The 28-day water immersion strength of the EMR100 can reach 38.3 MPa, and its water resistance coefficient was 82.10%. The appropriate doping of EMR can improve the pore structure of the specimens, reduce the porosity and refine the pore size distribution. Carbon emission per unit compressive strength and cost per unit compressive strength were used as evaluation indices of environmental and economic benefits. A high dosage of EMR-incorporated MOC resulted in low cost and carbon emission, especially the strength of the specimen after water immersion as a strength index. Taking into account the strength after 14 days of air curing and 28 days of water immersion, the advantages of cost per unit compressive strength and carbon emission per unit compressive strength of EMR100 were further extended and reduced by 86.23% and 22.15% respectively compared to the benchmark group. The heavy metal curing of EMR was evaluated by ion leaching test, and the result showed that MOC effectively cured the heavy metal ions in EMR and reduced the environmental risk of EMR. The good performance of EMR in MOC systems not only provides an effective breakthrough for the efficient utilization of EMR and its heavy metal curing, but also effectively improves the performance of MOC and reduces the production cost.

Design, Fabrication, and Test of a Prototype of Matrix Heat Exchanger for Cryogenic Distillation of Hydrogen Isotopes

The following properties are needed to increase the efficiency of refrigeration, liquefaction, and cryogenic separation cycles: Heat exchangers must have high effectiveness doubled by high compactness; small temperature differences between incoming and outgoing flows must be ensured to increase efficiency; there must be a large heat transfer surface, relative to the volume of the heat exchanger, to minimize heat loss; there must be a high heat transfer rate to reduce the transfer area; there must be a small pressure drop to reduce compression costs; and there must be high reliability with minimal maintenance. All these properties are entirely fulfilled by the designed matrix heat exchangers (MHEs). This paper presents the results of the research program developed by the team of the Cryogenic Laboratory from INC-DTCI ICSI Ramnicu Valcea, which included procedural stages of the realization and preliminary results of the characterization of the MHE-type heat exchanger in a narrow range of values to achieve a proper solution for a heat exchanger to be used for cryogenic purposes, such as cooling the gas mixture at the entrance of a distillation column of hydrogen isotopes and running at low pressure (typically regimes of 0.5 to 2.0 bars) and flows. Within several experimental campaigns, different assembly and testing techniques of the matrix heat exchanger (MHE) prototype were performed to achieve numerical data for the temperature and pressure drops along the heat exchanger and to verify ANSYS Fluent numerical simulation results. The results showed that for the designed and tested MHE prototype, a temperature drop of up to almost 230 K can be obtained at the established parameters correlated with pressure losses within a few millibars (the maximum recorded pressure drop is 80 mbars), small dimensions (64 mm high), and accessible weight (up to 2000 g).