Optimal Results Research Articles

SIMULATION ANALYSIS TO FORECAST PROGRESS AND OPTIMIZE RESOURCE UTILIZATION FOR MATERIAL TRANSPORTATION ACTIVITIES IN THE CONSTRUCTION PROJECT ON PHU QUY ISLAND

This article presents the main results of using a simulation tool to predict time and optimize the resource utilization for the transportion of materials processes in the construction project on Phu Quy island. A simulation model, which includes activities of material transfer processes, has been established and developed based on the EZStrobe simulation program. Various simulation scenarios with different resource usage options have been analyzed. The simulation results are also compared and evaluated with real-world project data. It indicates that for both productivity, time and cost, the option of using two 50-ton cranes at the dock; two 25-ton cranes at the storage yard and four trucks will be the best solution. The results of the study demonstrated the effectiveness of the simulation program, which may help managers choose the resource allocation plan and apply necessary changes to obtain the optimum results in terms of production and cost efficiency for the transportion of contruction materials on the island.

Emergency treatment of pelvic ring injuries: state of the art.

High energy pelvic injuries sustain significant mortality rates, due to acute exsanguination and severe associated injuries. Managing the hemodynamically unstable trauma patient with a bleeding pelvic fracture still forms a major challenge in acute trauma care. Various approaches have been applied through the last decades. At present the concept of Damage Control Resuscitation (DCR) is universally accepted and applied in major trauma centers internationally. DCR combines hemostatic blood transfusions to restore blood volume and physiologic stability, reduced crystalloid fluid administration, permissive hypotension, and immediate hemorrhage control by operative or angiographic means. Different detailed algorithms and orders of hemostatic procedures exist, without clear consensus or guidelines, depending on local traditions and institutional setups. Fracture reduction and immediate stabilization with a binder constitute the basis for angiography and embolization (AE) or pelvic packing (PP) in the hemodynamically unstable patient. AE is time consuming and may not be available 24/7, whereas PP offers a quick and technically easy procedure well suited for the patient in extremis. Resuscitative endovascular balloon occlusion of the aorta (REBOA) has also been described as a valuable adjunct in hemostatic non-responders, but merely constitute a bridge to surgical or angiographic hemostasis and its definitive role in DCR is not yet clearly established. A swift algorithmic approach to the hemodynamically unstable pelvic injury patient is required to achieve optimum results. The present paper summarizes the available literature on the acute management of the bleeding pelvic trauma patient, with emphasis on initial assessment and damage control resuscitation including surgical and angiographic hemostatic procedures. Furthermore, initial treatment of open fractures and associated injuries to the nervous and genitourinary system is outlined.

The Influence of Varying Ar/O2 Gas Ratio with Catalyst-Free Growth by Homemade Thermal Evaporation Technique

A nanostructured zinc oxide (ZnO) with different percentages of argon and oxygen gas flow rate was deposited on a silicon wafer by a simple hot tube thermal evaporation technique. The effect of different percentages of gas flow rate on the crystal structure, surface morphology and optical properties were characterized using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) and RAMAN spectroscopy, respectively. The changes of morphologies from FESEM were significant where the grown ZnO nanostructures show three different shapes which are nanotripods, nanoclusters and nanorods at 5%, 10% and 25% of oxygen gas, respectively. EDX results revealed that Zn and O elements have a major percentage in the sample indicating a composition has high purity of ZnO. XRD patterns displayed the most intense diffraction peak of ZnO at (101), which exhibited a single crystalline hexagonal structure with preferred growth orientation in the c-axis. RAMAN scattering study found that synthesized ZnO shows the high intensity of E2 mode and low intensity of E1 mode attributed to all the samples having good crystal quality containing fewer structural defects. In conclusion, the E15 sample with a 25% oxygen gas flow rate was selected as an optimum result for synthesizing a homogenous surface and high crystallinity of ZnO by using a hot tube thermal evaporation process. This work can enhance the development of ZnO production in various applications.

Multifrequency Ultrasound-Based Predictive Method for Biodiesel Production

Fossil fuel price continuous growth invites to look for alternative solutions to fuel for internal combustion engines. One of the most accepted options is biodiesel. In the present study, the multifrequency ultrasound-assisted synthesis of Sinapis alba oil biodiesel has been tested. For this purpose, an ultrasonic probe working at 20 kHz and an ultrasonic reactor with interchangeable transducers of discrete frequencies (195 kHz, 578 kHz, 861 kHz and 1136 kHz) have been used. For the probe, a multi-response optimisation has been carried out, setting methanol-to-oil molar ratio at 5.5:1. Optimal results were provided by 1.42 percentage weight (wt%) of catalyst after approx. 10 min of ultrasonication. In case of transducers, oil-to-biodiesel conversion needed an ultrasonication time of 15 min. Overall, when ultrasound frequency increases, oil-to-biodiesel conversion slightly improves. In conclusion, this work provides a predictive method to produce biodiesel under ultrasonication conditions, at different frequencies, in batch mode. Resulting biodiesel meets European standard requirements.

OPC UA-based Force Control for Deep Rolling with Mechanical Tools

Deep rolling can increase the service life of components under cyclic loads. This is achieved by plastic deformation of the component surface using a roller. The degree of plastic deformation depends on the rolling force. For a maximum increase in service life, the rolling force applied to the roller must stay within defined limits. When performing deep rolling using mechanical deep rolling tools, the rolling force is applied via an elastic element such as a leaf spring. The deep rolling force therefore depends on the deflection of leaf spring. It varies when the workpiece bends or has a varying diameter. These variations in the deep rolling force are not desired. They must be reduced to achieve optimum process results. To achieve this, a novel deep rolling force control for mechanical deep rolling was introduced in this paper. To control the rolling force, the force was measured with a sensory tool and machine tool axes were adjusted accordingly. The adjustment of the axes was implemented using the OPC UA standard. It is shown that this can reduce the force error during mechanical deep rolling by 90%. This ensures a constant process result and improves the mechanical deep rolling process.

Transfer learning: classifying balanced and imbalanced fungus images using inceptionV3

Identifying the genus of fungi is known to facilitate the discovery of new medicinal compounds. Currently, the isolation and identification process is predominantly conducted in the laboratory using molecular samples. However, mastering this process requires specific skills, making it a challenging task. Apart from that, the rapid and highly accurate identification of fungus microbes remains a persistent challenge. Here, we employ a deep learning technique to classify fungus images for both balanced and imbalanced datasets. This research used transfer learning to classify fungus from the genera Aspergillus, Cladosporium, and Fusarium using InceptionV3 model. Two experiments were run using the balanced dataset and the imbalanced dataset, respectively. Thorough experiments were conducted and model effectiveness was evaluated with standard metrics such as accuracy, precision, recall, and F1 score. Using the trendline of deviation knew the optimum result of the epoch in each experimental model. The evaluation results show that both experiments have good accuracy, precision, recall, and F1 score. A range of epochs in the accuracy and loss trendline curve can be found through the experiment with the balanced, even though the imbalanced dataset experiment could not. However, the validation results are still quite accurate even close to the balanced dataset accuracy.

Novel biofuel blends for diesel engines: Optimizing engine performance and emissions with C. cohnii microalgae biodiesel and algae-derived renewable diesel blends

Fossil diesel is a significant global fuel; however, environmental concerns and resource scarcity necessitate alternative fuels. Third-generation microalgae biodiesel (MB), despite its carbon neutrality, leads to higher oxides of nitrogen (NOx) emissions and poor engine performance. Renewable diesel (RD), also known as hydrotreated vegetable oil (HVO), could reduce these issues. A quasi-dimensional multi-zone combustion model is employed in this study to look into how different fuel blends of diesel, C. cohnii MB, and algae-derived RD affect the performance, combustion, and emissions of a compression ignition (CI) engine. The study uses a 2000 rpm engine arrangement with different engine loads, and validates the computational analysis with an experimental test engine arrangement. The study aims to explore the potential of sustainable biofuels in CI engines. D70MB30 (70 vol% diesel, and 30 vol% MB) fuel blend leads to a higher ignition delay period (IDP) while lowering peak cylinder pressure (PCP) and peak heat release rate (PHRR) compared to D100; however, when RD is added to diesel-MB fuel blends, it reduces IDP and increases PCP and PHRR. Brake specific fuel consumption (BSFC) for the D70MB30 blend rises by 5.28–8.9 %, while brake thermal efficiency (BTE) reduces by 0.98–4.27 %. However, RD in MB blends reduces BSFC by 1.57–3.41 % and marginally enhances BTE, resulting in greater fuel economy and efficiency. D70MB30 fuel blend results in higher specific carbon dioxide (CO2) emissions and oxides of nitrogen (NOx) emissions while lowering particulate matter (PM) and smoke emissions compared to neat diesel due to its high intrinsic oxygen content. In contrast, RD with the MB blend reduces specific CO2 and NOx emissions; however, it increases PM and smoke emissions due to the NOx-PM trade-off. The optimum results occur with a full load and D70MB15RD15 (70 vol% diesel, 15 vol% MB, and 15 vol% RD) fuel blend. Compared to the D70MB30 blend, D70MB15RD15 reduces BSFC, specific CO2, and NOx by 2.15 %, ∼1%, and 8.37 %, respectively, while increasing PM emissions at 100 % load.

Transfer learning: classifying balanced and imbalanced fungus images using inceptionV3

Identifying the genus of fungi is known to facilitate the discovery of new medicinal compounds. Currently, the isolation and identification process is predominantly conducted in the laboratory using molecular samples. However, mastering this process requires specific skills, making it a challenging task. Apart from that, the rapid and highly accurate identification of fungus microbes remains a persistent challenge. Here, we employ a deep learning technique to classify fungus images for both balanced and imbalanced datasets. This research used transfer learning to classify fungus from the genera Aspergillus, Cladosporium, and Fusarium using InceptionV3 model. Two experiments were run using the balanced dataset and the imbalanced dataset, respectively. Thorough experiments were conducted and model effectiveness was evaluated with standard metrics such as accuracy, precision, recall, and F1 score. Using the trendline of deviation knew the optimum result of the epoch in each experimental model. The evaluation results show that both experiments have good accuracy, precision, recall, and F1 score. A range of epochs in the accuracy and loss trendline curve can be found through the experiment with the balanced, even though the imbalanced dataset experiment could not. However, the validation results are still quite accurate even close to the balanced dataset accuracy.

Evaluating the durability performance of concrete containing clastic sand and GGBS

The manufacturing process of materials utilized in concrete production has environmental implications. The production of cement releases significant amounts of greenhouse gases, while the extraction of aggregates and sand poses challenges to the natural environment. To minimize the aforementioned challenges researchers are suggested to utilize industrial by-products as a partial alternative for these materials Fly ash, stone dust, GGBS, silica fume, and metakaolin are widely utilized alternatives to construction materials. The specific use of clastic sand as a partial substitute for fine aggregate has recently gained popularity . However, studies on the characteristics of concrete prepared using cementitious materials and clastic sand are very few. In this work, the effect of clastic sand with ground granulated blast furnace slag concrete is being investigated. The GGBS is added in place of cement from 0% to 45%. Further, clastic sand is added in different proportions in GGBS concrete. The electrical resistivity, water absorption, acid attack, and micro-structural studies are carried out on all mixes to know the durability properties. The results confirm that the addition of GGBS as a cementitious material enhances durability. The inclusion of 35% of GGBS as a substitute for cement is optimum for enhancing durability. Further, the inclusion of 35% GGBS as a cement substitute and 20% clastic sand shows a dense matrix and optimum results in enhancing durability. This is due to the pozzolanic activity of GGBS and clastic sand works as filler materials. This investigation suggests utilizing clastic sand along with GGBS as a cementitious material.

Penggunaan Kapur Tohor dan Abu Vulkanik pada Bata Ringan Terhadap Berat Jenis, Daya Serap Air, dan Kuat Tekan

Light brick is a material commonly used in building walls besides red brick. Quick lime and volcanic ash were used in this research as substitute materials for making CLC lightweight bricks. This research aims to analyze using quicklime as a cement substitute and volcanic ash as a sand substitute to test density, water absorption capacity, and compressive strength. Light brick testing refers to the SNI standards for wall masonry. This research also compares the production costs of substitute lightweight bricks with conventional ones. The method used is quantitative experimentation and data analysis techniques using regression analysis. The influencing variable in this research is the independent variable, namely the use of volcanic ash: quicklime in variation A 0%: 0%, variation B 9%: 15%, variation C 9%: 30%, and variation D 9%: 45%. Based on the test results, it can be concluded that using volcanic ash affects increasing density and compressive strength and reduces the value of water absorption capacity. The optimum test results were in Variation D with an average density value of 956 kg/m3, water absorption value of 17%, and compressive strength value of 2.08 MPa.

Optimization of the levels of ginger extract, palm oil and glucose syrup on the sensory quality of ginger yema

Ginger yema is a product of Guio-ang MPC cooperative of Guindolman, Bohol, Philippines. Yema may also be called a custard candy as it is mainly made of egg yolk, sugar and milk. The yema product made by Guio-ang MPC cooperative uses these same common ingredients with added ginger extract and glucose. To improve and enhance the sensory quality of the aforesaid product, an optimization study on the ingredients namely ginger extract, palm oil and glucose syrup was conducted. Response Surface Methodology (RSM) was used to determine the effect of the different levels of ingredients on the product’s sensory quality. Statistical analysis revealed that the linear and quadratic term of palm oil and glucose syrup levels significantly affect the color, hardness, chewiness and general acceptability of ginger yema. The quadratic term of ginger extract and palm oil significantly decreased the oiliness acceptability. Significant reduction in toothpacking acceptability was observed in the linear term of the glucose syrup level. The interaction of palm oil and ginger extract had a negative significant effect on the color, while the interaction of glucose syrup level and ginger extract significantly affected the hardness and toothpack. The interaction of the glucose syrup level and palm oil significantly affected the product’s hardness, chewiness and general acceptability as well. The superimposed contour plots of all responses revealed the optimum result for color, hardness, chewiness and general acceptability at 14.75% w/w ginger extract, 12.00% w/w palm oil, and 12.20% w/w of glucose syrup.

Optimization of Spray Characteristics of Full Cone Nozzles Used in Pesticide Application Using the Taguchi Method

The present study aims to reduce the amount of pesticide that can be released into environment, soil, air, and water by minimizing the type of nozzle and the use of excess pesticides by making use of the Taguchi method. For this purpose, studies were carried out to determine the spray characteristics of the pesticide. The sodium fluorescein was used in the experiments. In this study, the effects of the nozzle-to-surface distance (spray height), spray pressure, nozzle orifice diameter, and nozzle position angle on the droplet diameter and flow characteristics were investigated using the Taguchi method. The mean diameter values were determined first. Then, the volumetric median diameter (VMD) was considered as performance parameter and L9(34) orthogonal sequence was chosen as the experimental plan for four parameters that were determined. Calculating the VMD considered as the performance characteristics, optimum results were obtained using 6 bar spray pressure, 100 mm spray height, 30o nozzle position angle, and 1.10 mm nozzle orifice diameter. The VMD values were calculated using the image processing method and the effects of the parameters on the droplet diameter were interpreted using charts.

Dynamic Prediction of Total N and P Contents in Slurry from Dairy Farms under Different Treatment Processes Using Near-Infrared Spectroscopy

Nutrient content fluctuation in dairy production slurry is highly influenced by the various treatment processes applied in the Chinese dairy sector. The dynamic measurement of these contents is critical for the practical and efficient field application of slurry subjected to various processes. In the study, a total of 715 slurry samples were collected from 24 intensive dairy farms in Tianjin subjected to three typical treatment processes. Descriptive statistical analysis, principal component analysis, and partial least square regression were used to investigate the variation in total nitrogen (TN) and total phosphorus (TP) contents, spectral characteristics, and the performance of the prediction model of the slurry under the processes, respectively. Results revealed significant differences in both TN and TP contents along with the spectra for the slurry subjected to different treatment processes. All the inter-process models showed poor performance, and the results were worse compared to the intra-process models. Among the intra-process models for TN, the optimally performing models were the Pac fusion model (R2pred = 0.82; RPD = 2.38) and the single model Pa (R2pred = 0.83; RPD = 2.31). Among the intra-process models for TP, the optimum results were seen for Pab (R2pred = 0.77; RPD = 2.07) and Pa (R2pred = 0.79; RPD = 2.30). Taking different treatment processes into consideration is essential to establish flexible models that can be adaptive for diversified scenarios. This would be helpful to improve the tracking monitor measures, efficiently guide the land application of slurry, and support the sustainable development of animal farming and environmental conversation.

Exploratory study on experimental and prediction based stress-strain behaviour of corroded prestressing steel strands

Prestressing steel strands have been extensively used in recent years due to the increased popularity of prestressed concrete structures. However, the corrosion of strands has a detrimental effect on these structures. This necessitates a detailed investigation of the mechanical properties of the corroded strands and to understand their influence on the strength of these structures. Therefore, in this paper, a systematic attempt has been made to study the mechanical properties of corroded steel strands corroded using the accelerated corrosion method. Initially, the tensile test was conducted on these corroded steel strands to study the mechanical properties of the strands and X-ray diffraction analysis was done on the corrosion products of these corroded steel strands. Then, resilient backpropagation with backtracking neural network based prediction models were developed to predict the ultimate strength of the corroded strands. The experimental results showed that an increase in the corrosion level reduces the ultimate stress, yield stress, breaking stress and the corresponding strains of the strand. The proposed prediction models give optimum results of cost functions for ultimate stress and ultimate strain predictions. The comparison study of ultimate stress-strain results obtained from the proposed prediction models showed remarkable performance with the experimental results.

Stochastic optimal tuning for flight control system of morphing arm octorotor

PurposeThis study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the effect of morphing and to improve autonomous flight performance.Design/methodology/approachThis study aims to design and control the octorotor flight control system with stochastic optimal tuning under morphnig effect. For this purpose, models of different arm lengths of the octorotor were drawn in the Solidworks program. The morphing was carried out by simultaneously lengthening or shortening the arm lengths of the octorotor. The morphing rate was estimated by using simultaneous perturbation stochastic approximation (SPSA). The stochastic gradient descent algorithm, which is frequently used in machine learning, was used to estimate the changing moments of inertia with the change of arm lengths. The proportional integral derivative (PID) controller has been preferred as an octorotor control algorithm because of its simplicity of structure. The PID gains required to control both longitudinal and lateral flight were also estimated with SPSA.FindingsWith SPSA, three longitudinal flight PID gains, three lateral flight PID gains and one morphing ratio were estimated. PID gains remained within the limits set for SPSA, giving satisfactory results. In addition, the cost index created was 93% successful. The gradient descent algorithm used for the moment of inertia estimation achieved the optimum result in 1,570 iterations. However, in the simulations made with the obtained data, longitudinal and lateral flight was successfully carried out.Originality/valueOctorotor longitudinal and lateral flight control was performed quickly and effectively with the proposed method. In addition, the desired parameters were obtained with the optimization methods used, and the longitudinal and lateral flight of the octorotor was successfully carried out in the desired trajectory.

Influence of fermentation conditions, and the blends of sorghum and carrot pulp supplementation on the nutritional and sensory quality of tef injera

Tef [Eragrostis tef (Zucc.) Trotter], an ancient cereal primarily grown in Ethiopia, is becoming increasingly popular worldwide due to its high iron content and gluten-free nature. However, it has been reported that injera produced only with tef flour lack certain vital nutrients. Therefore, this specific study was conducted to supplement tef injera with other food materials of better nutritional value and compensate its expensive market price with sorghum cereal flour. The effect of fermentation conditions, and the sorghum and carrot pulp blending ratio on the nutritional value and sensory quality of tef injera was investigated. The factorial approach of the experimental design was conducted considering the nutritional value and sensory quality of the injera made of three main blending ratios of tef, sorghum, and carrot (60% tef: 30% sorghum: 10% carrot pulp, 45% tef: 45% sorghum: 10% carrot pulp and 30% tef: 60% sorghum: 10% carrot pulp) as experiential variables. The raw materials and injera were characterised for their proximate composition, physicochemical property, mineral composition, microbial analysis, and sensory attributes, using standard methods. The results of the study show that fermentation conditions and blending ratios have a significant effect on the nutritional, anti-nutritional, mineral content, microbial quality, and sensory properties of blended injera products, where higher values of ash, crude protein, crude fat, Total titratable acidity (TTA), Fe, Zn, and Ca (2.30%, 11.34%, 2.62%, 3.53, 32.97 mg/100 g, 2.98 mg/100 g and 176.85 mg/100 g, respectively) were analyzed for the co-fermented injera sample. In addition, a lower microbial count was observed in co-fermented injera samples, whereas microbial counts in injera samples prepared from carrot pulp-supplemented dough after the co-fermentation of tef and sorghum flours were observed to be higher. The injera product made using blending ratio of 60% tef: 30%sorghum: 10% carrot co-fermented was found to be the optimum result due to its very good nutritional improvement (i.e., reduction of some anti-nutritional factors, microbial contents, pH and increased contents of some minerals, crude protein, crude fat, TTA and improved most of the sensory quality of the supplemented injera product). According to this study, sorghum and carrot supplementation on tef could improve the nutritional value of injera while also providing an instant remedy for the growing price of tef.

Efficient minimum blind area model for system and interference uncertainty

AbstractIn the anti‐interference of broadband communication radio, interference cancellation performance is seriously affected by the uncertainty of the working frequency selection of the communication system and the direction of hostile interference. The closed‐form solution of the interference cancellation weight value and the signal‐to‐interference noise ratio after the cancellation are derived and simplified to clarify the factors affecting interference cancellation quality. Then, the efficient blind area criterion is established for the low computational complexity in view of cancellation quality, which combines the radio communication index and anti‐interference demand index. Based on this criterion, the minimum blind area model is proposed for robust performance. The experimental results in the auxiliary antenna spacing optimisation are consistent with the theoretical analysis, verifying the effectiveness of the proposed model in dealing with uncertain communication frequency and interference direction. It is very promising in communication interference cancellation.

Erosive wear and topographical study of zinc-aluminum based composite reinforced with in-situ formed ZrB2 particles

The present study deals with the erosive wear behaviour of a zinc-aluminum (ZA) alloy and composite in the slurry medium. The effects of reinforcement of zirconium diboride (ZrB2) particles in ZA alloy, as well as the impingement angle and duration of erosion wear responses have been studied. The slurry composition was prepared with 1.5 L of water and 500 g silica of a size range of 350–450 μm. The erosion tests are performed at a speed of 600 rpm for varying durations (20–80 h) and impingement angles (30°–90°). The erosive wear responses of the samples have been analyzed in terms of distinct features of their micro constituents like ZrB2 and the material removal mechanism in a prescribed set of conditions. A significant decrease in composite erosion compared to ZA alloy has been observed. With increased duration, both alloy and composite show increased erosive wear. Obtained results revealed that the composite shows 60–80 % less erosive wear than ZA alloy on operating conditions. The optimum results in wear have been observed at 45° for alloy and 60° for composite. Investigating topographical aspects using scanning electron microscopy and atomic force microscopy revealed that ZrB2 reinforcements resulted in smoother topography and reduced erosive wear.

Overview: Using Hybrid Energy System for Electricity Production Based on the Optimization Methods

Renewable energy systems are mostly used in the world due to their inexhaustible and non-polluting production. As a result of a large utilization of these energy sources in different areas, the electricity production rate is increasing every day. Previous studies clarified uses, modeling, configuration, energy management operation, and optimization objectives based on different energy sources. For this reason, this paper focuses on an overview of multi energy systems as renewable and conventional power sources with the integration of an energy storage system coupled to the on-off electrical network. Furthermore, a survey is done regarding global energy production, configuration energy systems, energy storage systems, power management strategies, and optimization methods based on different hybrid energy systems. Multiple optimization approaches have been implemented to reach the global best solution for the hybrid power systems. To ensure the best optimization result, it is preferable to take hybrid optimization methods into consideration. These methods have been invented recently and have proved their efficacy and performance mainly in power systems.

Properties of concrete containing spent garnet as fine aggregate replacement

Abstract The use of river sand as a construction material has become a critical concern in many countries. Excessive mining for concrete production is one of the main issues that lead to environmental pollution. Simultaneously, environmental concern over discarding spent garnet from industry have led to research on using it as a partial replacement for fine aggregate in concrete. Different mixtures incorporating 10 %, 20 %, and 30 % spent garnet were studied to assess their impact on concrete’s workability, mechanical strength, and durability. This study used a concrete mix design to create concrete mixes for 48 cubes. Three types of tests such as slump, compressive strength, and water absorption test were conducted to evaluate the concrete’s properties. The findings indicate that as the amount of spent garnet used in concrete increases, the concrete becomes more workable. The optimum strength results were achieved when 20 % of the fine aggregate was replaced with spent garnet. Furthermore, concrete with up to 20 % spent garnet had lower water absorption compared to the control mix. Utilizing spent garnet as a substitute for sand in construction not only fosters sustainability but also addresses the challenge of effective waste disposal.