Mixture Proportions Research Articles

The mathematical model for the optimization of compressive strength of sawdust ash geopolymer concrete

Geopolymer concrete offers an eco-friendlier option compared to traditional cement, as it lowers greenhouse gas emissions during production. It consists of an alkaline solution with sodium or potassium silicate and sodium or potassium hydroxide, as well as a source material abundant in silica and alumina. For this study, thirty geopolymer concrete samples were produced in the lab using a mix design approach from Scheffe’s (5,2) model. The focus of the research was on maximizing the compressive strength of the concrete, especially when incorporating sawdust ash as the source material. The findings indicated that subjecting sawdust ash to pyrolysis in the absence of oxygen significantly impacts its pozzolanic properties and, consequently, the characteristics of the concrete. The research determined the optimal compressive strength of geopolymer concrete incorporating sawdust ash to be 21.673 MPa, along with specific concentration ratios of NaOH, Na2SiO4 to NaOH, sawdust ash in the binder, water to binder, and activator to sawdust ash at 10.5415, 2.0446, 38.6307, 0.0363, and 2.5882 respectively. Furthermore, MATLAB-based computer programs were utilized to optimize and forecast the ideal mixture proportions for sawdust ash-based geopolymer concrete.

Synthesis of geopolymer mortar from biomass ashes and forecasting its compressive strength behaviour

The global warming dilemma raised an exigency toward sustainability in the construction industry and compelled scientists to hunt for alternative binders in construction materials. The, geopolymerization as a spectacular technology has arisen as a looming solution to this dilemma. This work assesses the features of geopolymer mortar developed with both industrial and agricultural wastes at ambient temperature curing. The geopolymer mix proportion was evolved in this study using main precursor material as fly ash, ground granulated blast furnace slag (GGBFS), sugarcane bagasse ash (SCBA) or rice husk ash (RHA). Workability and mechanical properties, including compressive strength, flexural strength, and split tensile strength of different mortar mixes with various percentages of RHA and SCBA for 365 days, were evaluated. Geopolymer mortar with 10 % SCBA and 5 % RHA achieved improvements of 25 % and 13.91 % in compressive strength, 10.6 % and 3.5 % in flexural strength, and 35 % and 16.8 % in split tensile strength, respectively. Good geopolymer gel formation is clearly evident from the SEM images of SCBA mortar. The main polymeric bonds Si–O–Al and Si-O-Si are also identified using FTIR. To assess the efficacious use of biomass ashes, resistance to chemical attack using H2SO4, HCl, Na2SiO3, and NaCl solutions for 365 days was studied. It was revealed that SCBA incorporated geopolymer mortar specimens achieved good resistance compared with RHA geopolymer mortar. The relation between the ambient temperature cured geopolymer specimen compressive strength at 28 days and 365 days chemical solution curried geopolymer specimen compressive strength find out using python and obtained R2 values more than 95 %. Also, this research proposed various machine learning techniques such as long short-term memory, support vector regression, random forest regression, XGBOOST, and AdaBOOST algorithms for the prediction of compressive strength of geopolymer using 724 mixture proportions with diverse curing temperatures and varying ages. The XGBOOST algorithm achieved the highest R² value of 0.92, demonstrating its effectiveness for the strength prediction.

Understanding the synergistic geopolymerization mechanism of multiple solid wastes in ternary geopolymers

The use of ground granulated blast furnace slag (GBFS), fly ash (FA) and steel slag (SS) to form ternary geopolymers consumes several industrial solid wastes and produces high-performance construction materials. However, the unexplored synergistic geopolymerization mechanism of multiple solid wastes limits the design of high-performance ternary geopolymers. This study investigated the synergistic mechanism through testing the macroscopic performances such as unconfined compressive strength (UCS), final setting time (FST) and fluidity, and characterizing the microscopic structure of ternary geopolymers with different mixture proportions. In addition, the influence of variables on strength development of ternary geopolymers is analyzed by developing machine learning models. Results reveal that the highest strength of ternary geopolymers was achieved at a ratio of FA to GBFS to SS of 3:5:2, and alkali activator to precursor materials of 0.08. Addition of 20 % SS refines the pore network, reducing cumulative and detrimental pore volumes, thus enhancing compressive strength. In addition, the SS addition extends the heat generation peak during geopolymerization due to its slower reaction kinetics. Material components (Na/Al, Si/Al, Ca/Si) have a significant influence on UCS, with Na/Al ratio being the most sensitive variable. The study provides a new approach for utilization of bulk industrial wastes.

Pumping-less 3D concrete printing using quick nozzle mixing

Nozzle technologies for 3D concrete printing have been evolving to balance the conflicting demands of buildability and pumpability. This study introduces a simplified approach that eliminates the need for pumping by developing a customized system, the parameters of which were evaluated. The effect of process parameters (i.e., the flow rates of liquid and solid materials) and mixture proportions (i.e., the ratios of powder to sand and liquid to solid) on the extrudability and print quality was explored. Furthermore, the mechanical properties and microstructure of concrete printed using the Quick Nozzle Mixing system were examined. Results show that Quick Nozzle Mixing Technology not only enables high-quality printing but also exhibits the potential for achieving better process efficiency and higher aggregate content. The water-to-solid ratio is a critical factor influencing extrudability and buildability. Due to anisotropy caused by this new method, printed concrete has a lower strength than cast concrete.

Evaluation of meadow fescue grass cultivars seeded with alfalfa in New York state

AbstractAlfalfa–grass mixtures sown in the northeastern United States provide high‐quality dairy forage, and meadow fescue (Festuca pratensis Huds.) may improve the quality of these mixtures. Our objectives were to evaluate competitiveness and nutritive value of nine meadow fescue (MF) cultivars in New York State at spring harvest. Three farms, two in central New York State and one in northern New York state, were used. Conventional alfalfa (Medicago sativa L.) was sown (15 lb acre−1) to nine MF cultivars (three tetraploid and six diploid) and one tall fescue Lolium arundinaceum (Schreb.) ‘Darbysh’ cultivar in a randomized complete block design with four field replicates at each field site at three seeding rates (1, 2, and 3 lb acre−1). Grass proportion in mixtures was estimated visually. Grass samples were collected shortly before first harvest and analyzed for neutral detergent fiber, neutral detergent fiber digestibility (NDFD), acid detergent fiber, in vitro digestibility, and crude protein. Most meadow fescue cultivars maintained a grass proportion between 20%–45% across farms and growing seasons when seeded at 1lb acre−1. Seeding rates above 1lb acre−1 resulted in grass proportions above the recommended 20–30% grass proportion rate. Drought in early 2022 resulted in an average drop in grass percentage of 16.9% units for meadow fescue in mixtures, compared to 2021. Nutritive value of cultivars varied among farms and over growing seasons. Meadow fescue cultivars averaged 2.7% units higher NDFD than tall fescue, and cultivars with consistently high NDFD were Hidden Valley, SW Revansch, SW Minto, and Schwetra. Tetraploid cultivars averaged 4.0% units lower NDF compared to diploid cultivars, which is very advantageous for grass in alfalfa–grass mixtures.

Multi-objective optimization of cement-based systems containing marine dredged sediment

This study presents the integrated use of particle packing methodology and response surface methodology as an innovative mixture design for developing eco-friendly cement-based systems containing marine dredged sediment. The objective was to reduce the sand and cement contents of mortar mixtures for island applications, while maintaining the same properties as a reference mixture. The study examined three input variables for mixture design and optimization: sediment-to-total sand ratio ranging from 0.1 to 0.4, water-to-binder ratio ranging from 0.4 to 0.5, and cement paste content ranging from 0.35 to 0.45. As a result, three mixtures were developed based on three optimization objectives: (1) maintaining the same fresh and hardened properties as the reference (110 mm spread flow and 49.5 MPa strength); (2) maximizing the reduction of cement and sand contents with the use of a superplasticizer; and (3) maximizing the durability (as measured with the bulk electrical resistivity). The optimal mixture proportions showed reduced sand and cement contents up to 38 % and 15 %, respectively, with mechanical properties comparable to that of the reference. Moreover, capillary absorption and drying shrinkage of the optimized mixtures were reduced compared to the reference by up to 36 % and 16.5 %, respectively. It was evidenced that the combined use of mixture design methods can significantly contribute to the development of cementitious systems with balanced eco-efficiency and properties.

A new, standardized international Pacific Rim baseline for genetic stock identification (GSI) of Chinook Salmon

AbstractObjectiveGenetic stock identification (GSI) can be an effective tool for fisheries management, but development of reference baselines for species with broad geographic distributions can be challenging. Mixed‐stock fisheries for Chinook Salmon Oncorhynchus tshawytscha have utilized GSI analyses for decades with various genetic baselines, but these have largely become outdated with advances in technology that enable more efficient genotyping. Thus, our goals were to (1) create nested baselines of genotypic data for Chinook Salmon throughout their entire natural range using existing data from multiple sources and (2) evaluate the utility of those nested baselines to conduct accurate hierarchical GSI of mixture proportions or the stock identification of individual fish.MethodsIn this study, we compiled a large genetic baseline of single‐nucleotide polymorphism (SNP) markers for 389 populations that encompass the entire geographic range of Chinook Salmon. We used cross validation and realistic mixture simulations to test the accuracy of the baseline in generating GSI estimates.ResultWe demonstrated that a multi‐tiered assignment approach can provide high accuracy at both tier 1 (broadscale, with three coastwide reporting groups; 97.8% mean accuracy) and tier 2 (fine‐scale regional reporting groups; up to 97.7% mean accuracy) levels. Realistic mixture simulations showed that this multi‐tiered approach can provide highly effective GSI results for several common mixed‐stock fisheries applications in the Pacific Ocean.ConclusionThis new SNP baseline and the multi‐tiered assignment approach provide the most comprehensive rangewide GSI baseline for Chinook Salmon over any previous application and enable highly accurate estimates for GSI purposes.

Inference of Locus-Specific Population Mixtures from Linked Genome-Wide Allele Frequencies.

Admixture between populations and species is common in nature. Since the influx of new genetic material might be either facilitated or hindered by selection, variation in mixture proportions along the genome is expected in organisms undergoing recombination. Various graph-based models have been developed to better understand these evolutionary dynamics of population splits and mixtures. However, current models assume a single mixture rate for the entire genome and do not explicitly account for linkage. Here, we introduce TreeSwirl, a novel method for inferring branch lengths and locus-specific mixture proportions by using genome-wide allele frequency data, assuming that the admixture graph is known or has been inferred. TreeSwirl builds upon TreeMix that uses Gaussian processes to estimate the presence of gene flow between diverged populations. However, in contrast to TreeMix, our model infers locus-specific mixture proportions employing a hidden Markov model that accounts for linkage. Through simulated data, we demonstrate that TreeSwirl can accurately estimate locus-specific mixture proportions and handle complex demographic scenarios. It also outperforms related D- and f-statistics in terms of accuracy and sensitivity to detect introgressed loci.

Technosol made with urban and industrial waste: Potential for improving soil quality and growing tree seedlings

This study evaluated the use of waste materials to produce Technosol, a "tailor-made" soil consisting of construction and demolition waste (CDW), solid waste from stone mining (WSM), natural soil (NS), and compost from plant pruning (CPP), for improving soil quality in forest recovery projects. Samples of CDW were characterized using X-ray fluorescence and X-ray diffraction. The potential of the Technosol as a substrate was assessed using a mixture of "Class A" CDW, WSM, NS, and CPP in the following proportions: (a) 10 % CDW + 42.5 % WSM + 42.5 % NS + 5 % CPP, (b) 20 % CDW + 37.5 % WSM + 37.5 % NS + 5 % CPP, and (c) natural soil as a control. A randomized block design was used with nine treatments and three replications using 5.5 L pots. The experimental treatments consisted of two proportions of mixtures, natural soil, and three tree species: pioneer, Cecropia pachystachya, secondary, Handroanthus impetiginosus and climax, Copaifera langsdorffii. The activity of the enzymes β-glucosidase and arylsulfatase was determined in the Technosol and natural soil at the end of the experiment. During 180 days, the height of the plants and the diameter of the stem were determined at intervals of 30 days and, at the end of the experiment, the aerial part dry mass (leaves and trunk) and roots were evaluated. The Technosol constructed from the mixture (a) proved to be viable for improving soil quality, as indicated by a greater enzymatic activity compared to other soils, and for the growth of H. impetiginosus seedlings, showing the capacity to gain plant height over 180 days after planting.

Study on Improvement Measures for Construction Performance and Mechanical Properties of Cement Stabilized Porous Basalt

Abstract Cement stabilized porous basalt (CSPB) is prone to early agglomeration into lumps owing to the abundant pores and high moisture absorption of porous basalt, making it difficult to unload the mixture at construction sites in high temperatures and rainy areas. To study the construction performance of a CSPB mixture, a novel test method and a convenient device were proposed to test the workability of the cement stabilized macadam mixture, and the evaluation criteria and evaluation method of the workability were proposed based on the tilt angle test. The influencing factors of the workability of CSPB were investigated, and the results show that temperature, delay time, moisture absorption of aggregate, mixture proportion, and construction technology had significant influences on construction performance. Then measures were recommended to improve the construction performance of CSPB. Considering the influence of construction performance on mechanical strength, the effects of temperature, delay time, water reducer dosage, and cement dosage on the mechanical strength of CSPB were also investigated. The results show that temperature and delay time had significant influence on the mechanical strength. The results of this research are of great significance to the field construction of CSPB.

Drag reduction and degradation of binary polymer solutions

Polymer-induced drag reduction has yielded great potential benefits for industrial processes after more than 70 years of research. However, the limitation of low shear stability has hindered further applications. This study investigates the rheology, drag reduction rate (DR), and degradation of binary polymer mixtures comprising a rigid polymer (diutan gum, DG) and a flexible polymer (polyethylene oxide, PEO). The solutions all exhibited shear-thinning behavior, and the mixed solution was less viscous than the pure PEO or DG solutions at the total concentration of 100 ppm. When fixing the PEO concentration at 50 ppm, the mixed solution viscosity significantly increased with the DG concentration. The drag reduction performance of the pure PEO solution, pure DG solution, and various proportions of binary polymer mixtures was analyzed using an in-house rotor device. The DRs of the solutions increased with the Reynolds number (Re), and decreased with shearing time. The binary solution significantly improved the shear stability of the solution without loss of DR compared to the pure PEO solution. The theoretical model for molecular degradation in turbulent flow excellently fitted the experimental data of relative drag reduction with time. Furthermore, the synergistic interaction parameter was calculated, and it was positive for most cases in the mixtures. Additionally, when Re was fixed, the synergistic interaction parameter, related to the composition of binary polymer mixtures, initially decreased and then increased with time.

YADA - Reference Free Deconvolution of RNA Sequencing Data

Introduction: We present YADA, a cellular content deconvolution algorithm for estimating cell type proportions in heterogeneous cell mixtures based on gene expression data. YADA utilizes curated gene signatures of cell type-specific marker genes, either obtained intrinsically from pure cell type expression matrices or provided by the user. Method: YADA implements an accessible and extensible deconvolution framework uniquely capable of handling marker genes alone as inputs. Adoption barriers are lowered significantly by relying solely on literature-supported cell type-specific signatures rather than full transcriptomic profiles from purified isolates. However, flexible inputs do not necessitate sacrificing rigor - predictions match metrics of current methodologies through an integrated optimization scheme balancing multiple inference algorithms. Efficiency optimizations via compiled runtimes enable rapid execution. Packaging as an importable Python toolkit promotes community enhancement while retaining codebase extensibility. Result: Validation studies demonstrate that YADA matches or exceeds the performance of current deconvolution methods on benchmark datasets. To demonstrate the utility and enable immediate usage, we provide an online Jupyter Notebook implementation coupled with tutorials. Conclusion: YADA provides an accurate, efficient, and extensible Python-based toolkit for cellular deconvolution analysis of heterogeneous gene expression data.

Evaluating the Geotechnical Properties of Stabilized Problematic Soil by Utilizing Reed Ash and Lime Mixture

Stabilization of problematic soil poses a significant challenge in civil engineering projects, especially in regions with prevalent soft clay soils. This study was carried out to study the impact of using a blend of reed ash and lime on improving and stabilizing problematic soil. A sample of soil was obtained from a location in the south of Iraq, specifically in Al-Muthanna Governorate. The treatment involved adding different proportions of reed ash (3%, 5%, 7%, and 9.0% of the soil's dry weight) along with 5% lime, which was determined as the optimal percentage based on previous research. Various laboratory tests were conducted to assess the characteristics of the treated soil, including compaction and unconfined compressive strength (UCS). The findings indicated a notable enhancement in UCS and the maximum dry density (MDD). It was observed that UCS and MDD increased with increasing the reed ash and lime mixture proportion, reaching an optimal level. Beyond this percentage, the strength started to decline. It was found that the incorporation of lime and reed ash (5% lime and 7% reed ash) into the treated soil significantly improved its strength, up to about 10 times compared to untreated soil after 28 days of curing. This approach offers additional benefits, such as reducing environmental pollution by decreasing CO2 emissions during phases of production and providing cost savings because of the affordability of the materials used.

Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance. Additionally, the laboratory mix design process, which involves selecting aggregate gradation and binder content, is time-consuming and labor-intensive. To accelerate the traditional mix design procedure, this study presented a mix design procedure that can automatically determine gradation and binder content based on machine learning (ML) and a meta-heuristic algorithm. Specifically, ML approaches were employed to model the relationship between volumetric properties (mixture bulk specific gravity (Gmb) and air void (VV)) and both mixture component properties and mixture proportion, based on a dataset collected from literature with 660 mixture designs. Integrated with the prediction of ML models and the modified multi-objective grey wolf optimization (MOGWO) algorithm, an automatic asphalt mix design was proposed to pursue three goals, including VV, cost, and CO2 emission. The results indicated that least squares support vector regression (LSSVR) and eXtreme gradient boosting (XGBoost) achieved the highest prediction accuracies (correlation coefficient: 0.92 for VV and 0.96 for Gmb). The MOGWO algorithm successfully found the 26 optimal mix designs for the case of VV vs. cost vs. CO2 emission. Compared to the traditional laboratory design, the optimal mixture with VV of 4% achieves a cost saving of 2.46% and a reduction of 4.03% in carbon emission. The volumetric properties of the mixtures output by the approach also align closely with values measured in a laboratory.

Performance of Zero-Slump Concrete Made with Recycled Concrete Aggregate

Abstract Concrete with no slump that is typically used for prefabrication is known as zero slump concrete (ZSC). ZSC is sensitive to mixture proportion. Since coarse aggregate makes up the majority of the concrete volume, recycling concrete aggregates will be a great choice for reducing the amount of concrete waste. Therefore, the purpose of this paper is to analyze the impact of using coarse recycled concrete aggregate (RCA) in ZSC properties. Five mixes were manufactured, each with a different percentage of coarse RCA (0%, 25%, 50%, 75%, and 100%). Compressive strength, flexural strength, ultrasonic pulse velocity (UPV), dry bulk density, and water absorption of recycled aggregate ZSC were conducted at 7, 28 and 90 days. Experiments revealed that the inclusion of coarse RCA in ZSC degraded the quality of manufactured concrete. At 90 days, in comparison to the control mix, the minor drop was at 25% coarse RCA incorporation, which resulted in a 6.2%, 4.1%, 2%, and 2.4% drop in compressive strength, flexural strength, UPV, and dry bulk density, respectively, while there was a 24.4% increase in water absorption. The highest drop of recycled aggregate ZSC at 100% incorporation resulted in a 41.7%, 19.1%, 8.6%, and 7.6% drop in compressive strength, flexural strength, UPV, and dry bulk density, respectively, while there was a 158.8% increase in water absorption.

Proportioning of Oil Shale Ash for Sustainable 3D Printable Mortars

To achieve optimal strength and printability, mortars used in 3D printing typically contain high proportions of cement and other fine-grained powders. Consequently, the majority of mixtures used in 3D printing have high carbon footprint. Hence, there arises a critical need to study alternative supplementary cementitious materials aimed at reducing the environmental impact of mortars used in 3D printing. The use of oil shale ash as a partial substitute for cement not only addresses this issue but also presents an opportunity to repurpose waste from power plants in the Baltic states, where oil shale is intensively utilized.In this study, the influence on mechanical properties and durability of cement-based mortars was evaluated by substituting cement with oil shale ash in varying quantities. Specifically, 0% to 40% of cement mass was replaced with oil shale ash. Life cycle assessment (LCA) was performed for each mixture. By analyzing the material properties alongside the environmental impact for each mixture, the optimal percentage of substitute was determined.For the determination of the mechanical properties of each mixture, compressive and flexural strength tests were conducted on 3D printed samples in various directions, as well as on cast samples. To assess the durability of each mixture, freeze-thaw tests were performed on both 3D printed and cast samples.From the obtained results, we developed an algorithm that chooses the optimal mixture proportioning. Depending on material performance requirements set in the beginning, this algorithm gives the exact proportions of oil-shale ash and cement for the mixture, by taking into account both desired material properties and carbon dioxide emissions. As a result, an environmentally friendly cement-based mixture is obtained without losing the desired properties. By using this algorithm, it is possible to create a mortar with properties comparable to concrete with strength class C30/37 while reducing carbon emissions by 15% to 30%.

Utilizing Industrial Sludge Ash in Brick Manufacturing and Quality Improvement.

This research demonstrates changes in the behaviors and characteristics of sintered bricks while using industrial sludge ash (ISA) and waste glass (WG) as a replacement for clay in the brick manufacturing procedure. Owing to the limited amount of available land in Taiwan, it is becoming increasingly difficult to locate suitable sites for sanitary landfills, which is a common final disposal method for ash that is produced during thermal treatment in sludge factories. To meet the urgent need for land, the final waste disposal must convert this waste into a new resource. This research investigated the feasibility of using general industrial sludge ash waste, due to its abundance and high potential as a raw material in producing bricks. The result of this study shows that the bricks made from ISA and WG under a certain mixture proportion (ISA50%/WG40%/Clay10%) had excellent industrial potentials, such as compressive strength and water absorption rate. However, owing to the wide variety of components from different sources of ISA, the mixture proportion might vary accordingly. This study also analyzed the incineration index, proportion design, and process improvement, as well as investigating the possibility of increasing the total use of sludge ash as a resource. This study shows the potentials of utilizing wastes as raw materials in industrial manufacturing procedures. Therefore, more wastes can be tested and turned into resources in the future.

The Influence of Injector Nozzle Diameter on High-Density and Lean Mixture Combustion in Heavy-Duty Diesel Engines

In order to improve the fuel economy of heavy-duty diesel engines under high-load conditions, based on the combustion pathway model, it is proposed that the proportion of lean mixture with 0 < Φ < 1 is the most important spray characteristic affecting the overall diesel combustion process. Answering the question of how to increase the proportion of lean mixture inside the spray is the key to achieving the efficient and clean combustion of diesel engines. This paper investigated the mechanism of injector nozzle diameter on the in-cylinder air–fuel mixture and combustion process based on a high-density and lean mixture characteristic combustion strategy. The experimental results show that with an increase in nozzle diameter, the peak pressure and instantaneous heat release rate significantly increase, the combustion duration is shortened by about 20%, and the heat release becomes more concentrated. At 1200 rpm and IMEPg~2.3 MPa conditions, the indicated thermal efficiency increases by 1.3%, reaching a maximum of 51.5%. The numerical simulation results show that with the increase in nozzle diameter from 0.169 mm to 0.218 mm, the spray ejection momentum per unit time increases by 30%, the momentum transferred to the air by the spray increases, the oxygen transport process becomes more intense, and the air entrainment mass during the spray free development stage increases by 42%. The proportion of lean mixture inside the spray throughout the entire spray development process increases, resulting in an increase in the heat release rate of the lean mixture, making the overall combustion more intense and concentrated.

Machine learning guided iterative mix design of geopolymer concrete

Current mix design methods for Geopolymer concrete (GPC) require substantial efforts of trial-and-error experiments and is applicable only to those formulated by specific precursor materials. In this work, a machine learning (ML) guided mix design method for GPC is proposed, which can considerably reduce the experimental workload and be versatile with a broad range of precursor materials. First, a database for the slump and compressive strength of GPC was established, and ML prediction models were developed with these as objectives. Subsequently, the mix design for GPC was conducted using the particle swarm optimization (PSO) algorithm. The designed mixture proportions underwent experimental validation, and if targets were not met, results were then used for model iteration until desired performance targets were achieved. The results showcase the excellent performance of the established slump and compressive strength prediction models, with an accuracy and coefficient of determination of 94 % and 0.95, respectively. The developed ML guided model effectively generates concrete mix achieving compressive strengths of 20 MPa, 40 MPa, and 60 MPa, while concurrently satisfying slump requirements. The experimentally validated results for the three designated target strengths after iterations were 25.2 MPa, 43.8 MPa, and 66.6 MPa, respectively. These positive results emphasize the ability of the proposed optimized mix design method to meet both the strength and workability targets in GPC via a minimum number of trail experiments.

Anaerobic Co-Digestion of Fish Sludge Originating from a Recirculating Aquaculture System

Anaerobic co-digestion (AcoD) of fish sludge (FS) with food waste (FW), and fruit and vegetable waste (FVW) for biogas and methane production was optimised in small-scale bioreactors, and batch and semi-continuous pilot-scale digesters, under mesophilic (37 ℃) conditions. An experimental mixture design was first applied to small-scale biomethane potential (BMP) tests, to determine the optimal mixture proportions of the AcoD of FS, FW, and FVW that maximise the specific methane yield (SMY in NmLCH4 gVS−1). The optimal mixture proportion was 67%FS:18%FW:19%FVW (w/w), producing 401 mLCH4 gVS−1, which was 8 times higher than the SMY when FS was mono-digested (48 mLCH4 gVS−1). The SMY achieved in batch pilot-scale digesters were 70–82% of methane yields obtained in BMP tests under the same operating conditions, with stable biogas production and no apparent inhibition during the batch run. Semi-continuous operation of the pilot-scale digester was undertaken with organic loading rates (OLRs) of 1, 2, and 3 gVSL-1d-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$gVS{L}^{-1}{d}^{-1}$$\\end{document}, provided intermittently. However, the digester did not achieve stable biogas production at all of the evaluated OLRs, due to the intermittent feeding and accumulation of volatile fatty acids (VFAs): Improved process stability was achieved at an OLR of 2 gVSL-1d-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$gVS{L}^{-1}{d}^{-1}$$\\end{document}, compared to OLRs of 1 and 3 gVSL-1d-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$gVS{L}^{-1}{d}^{-1}$$\\end{document}. Optimisation of the AcoD process resulted in attractive biomethane yields from FS with FW and FVW co-feeds, indicating that producing biogas from co-digestion of FS with relevant substrates is a valuable managing tool for FS, while simultaneously providing renewable energy. The work provides novel data that elucidated optimal proportions in which to combine FS, FW and FVW to obtain optimal biogas production, and provided important new information relevant for the scale up and continuous operation of an AD process for treating FS.Graphical