Multi-criteria Analysis Research Articles

An MCDM analysis of critical success criteria for medium and large construction projects in Australia and New Zealand

PurposeThe global construction industry has a history of poor project success, with evident and frequent overruns in cost and schedule. This industry is a highly interconnected and complex system in which the components, i.e. suppliers, contractors, end-users, and stakeholders, are delicately linked to each other, the community, and the environment. Therefore, defining and measuring project success can be challenging for sponsors, contractors, and the public. To address this issue, this study develops and analyzes a more comprehensive set of success criteria for medium and large construction projects.Design/methodology/approachAfter reviewing the existing literature, this study identified 19 success criteria for medium and large construction projects, which were categorized into five groups. The fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) method was used to gain further insight into the interrelationships between these categories and explain the cause-and-effect relationships among them. Next, this study applied the modified logarithmic least squares method to determine the importance weight of these criteria using the fuzzy analytic hierarchy process.Findings28 project managers working in the construction industries in Australia and New Zealand participated in this study. Results suggest that “project efficiency” and “impacts on the project team” are cause criteria that affect “business success,” “impacts on stakeholders,” and “impacts on end-users.” Effective risk management emerged as the most crucial criterion in project efficiency, while customer satisfaction and return on investment are top criteria in “impacts on end-users” and “business success.”Originality/valueAlthough numerous studies have been conducted on project success criteria, multicriteria analyses of success criteria are rare. This paper presents a comprehensive set of success criteria tailored to medium and large construction projects. The aim is to analyze their interrelationships and prioritize them thoroughly, which will aid practitioners in focusing on the most important criteria for achieving higher success rates.

Modeling Environmental Vulnerability for 2050 Considering Different Scenarios in the Doce River Basin, Brazil

Understanding climate change and land use impacts is crucial for mitigating environmental degradation. This study assesses the environmental vulnerability of the Doce River Basin for 2050, considering future climate change and land use and land cover (LULC) scenarios. Factors including slope, elevation, relief dissection, precipitation, temperature, pedology, geology, urban distance, road distance, and LULC were evaluated using multicriteria analysis. Regional climate models Eta-HadGEM2-ES and Eta-MIROC5 under RCP 4.5 and RCP 8.5 emission scenarios were employed. The Land Change Modeler tool simulated 2050 LULC changes and hypothetical reforestation of legal reserve (RL) areas. Combining two climate and two LULC scenarios resulted in four future vulnerability scenarios. Projections indicate an over 300 mm reduction in average annual precipitation and an up to 2 °C temperature increase from 2020 to 2050. Scenario 4 (RCP 8.5 and LULC for 2050 with reforested RLs) showed the greatest basin area in the lowest vulnerability classes, while scenario 3 (RCP 4.5 and LULC for 2050) exhibited more high-vulnerability areas. Despite the projected relative improvement in environmental vulnerability by 2050 due to reduced rainfall, the complexity of associated relationships must be considered. These results contribute to mitigating environmental damage and adapting to future climatic conditions in the Doce River Basin.

Make-or-Buy Policy Decision in Maintenance Planning for Mobility: A Multi-Criteria Approach

The ongoing technical innovation is fully involving transportation sector, converting the usual mass-transit system toward a sustainable mobility. Make-or-buy decision are usually adopted to assess different solutions in terms of costs-benefits to put in place strategic choices regarding in-house production or from an external supplier. This can also be reflected on maintenance operations, thus replicating a similar approach to transport companies involved. This paper aims to present a decision-making model by means of a multi-criteria analysis to lead make-or-buy choices adapted to maintenance. A brief introduction into the actual mobility context is provided, evaluating global and national trends with respect to the mobility solutions offered. Then, a focus is set on maintenance approaches in mobility sector and the need of a make-or-buy decision process is considered. The decision-making path is developed through a multi-criteria framework based on eigenvector weighing assessment, where different Key Performance Indicators (KPIs) are identified and exploited to assess the maintenance approach at stake. Results allow to compare the solution offered by the different scenarios considered. In particular, for the case study of interest a −35% decrease in maintenance specific cost and −44% in cost variability were found. Reliability of the fleet was kept at an acceptable level compared to the reference in-house maintenance (≥90%) while an increase in the Mean Time Between Failure was observed. For the purposes of a small company, the method can address the choice of outsourcing maintenance as the best. Finally, a general trend is then extrapolated from the analysis performed, in order to constitute a decision guideline.

Assessing the suitability of desalination techniques for hydraulic barriers

Seawater intrusion is a worldwide increasing challenge, which lowers the freshwater availability by salination of fresh groundwater resources in coastal areas. The abstraction-desalination-recharge (ADR) methodology can combat seawater intrusion, whereby desalination is hereby the key factor for the overall efficiency of aquifer remediation. Which desalination technique is suitable within ADR depends on several factors and was not discussed before. We use a multi-criteria decision analysis and cost analysis to compare nanofiltration, reverse osmosis, electrodialysis, and (membrane) capacitive deionization and show for three case scenarios which desalination technique is most suitable within ADR. Overall, electrodialysis, nanofiltration, and reverse osmosis have shown the best utility value for saline groundwater salinity of 1–10 g L−1, whereby electrodialysis is more suitable for lower salinities. The lowest desalination costs are calculated for nanofiltration and reverse osmosis with 0.3–0.6 € m−3 depending on specific energy costs. Even capacitive deionisation can be a suitable alternative for low, slightly saline groundwater (1 g L−1) if the technology readiness level and a lifetime of electrodes increase and material costs decrease. These new insights provide a data analysis, costs, and decision support for desalination which are needed for the holistic approach to counteract seawater intrusion.

Patients' Preferences for Sphingosine-1-Phosphate Receptor Modulators in Multiple Sclerosis Based on Clinical Management Considerations: A Choice Experiment.

Several sphingosine-1-phosphate receptor (S1PR) modulators are available in the US for treating relapsing forms of multiple sclerosis (RMS). Given that these S1PR modulators have similar efficacy and safety, patients may consider the clinical management characteristics of the S1PR modulators when deciding among treatments. However, none of the S1PR modulators is clearly superior in every aspect of clinical management, and for some treatments, clinical management varies based on a patient's comorbid health conditions (e.g., heart conditions [HC]). This study aimed to determine which S1PR modulator patients with relapsing-remitting multiple sclerosis (RRMS) would prefer based on clinical management considerations, and to estimate how different clinical management considerations might drive these preferences. Preferences were explored separately for patients with and without comorbid HC. A multicriteria decision analysis was conducted on S1PR modulators approved to treat RMS: fingolimod, ozanimod, siponimod, and ponesimod. Clinical management preferences of patients with RRMS were elicited in a discrete choice experiment (DCE) in which participants repeatedly chose between hypothetical S1PR modulator profiles based on their clinical management attributes. Attributes included first-dose observations, genotyping, liver function tests, eye examinations, drug-drug interactions, interactions with antidepressants, interactions with foods high in tyramine, and immune system recovery time. Preferences were estimated separately for patients with HC and without HC (noHC). Marginal utilities were calculated from the DCE data for each attribute and level using a mixed logit model. In the multicriteria decision analysis, partial value scores were created by applying the marginal utilities for each attribute and level to the real-world profiles of S1PR modulators. Partial value scores were summed to determine an overall clinical management value score for each S1PR modulator. Four hundred patients with RRMS completed the DCE. Ponesimod had the highest overall value score for patients both without (n=341) and with (n=59) HC (noHC: 5.1; HC: 4.0), followed by siponimod (noHC: 4.9; HC: 3.3), fingolimod (noHC: 3.4; HC: 2.8), and ozanimod (noHC: 0.9; HC: 0.8). Overall, immune system recovery time contributed the highest partial value scores (noHC: up to 1.9 points; HC: up to 1.2 points), followed by the number of drug-drug interactions (noHC: up to 1.2 points; HC: up to 1.7 points). When considering the clinical management of S1PR modulators, the average patient with RRMS is expected to choose a treatment with shorter immune system recovery time and fewer interactions with other drugs. Patients both with and without heart conditions are likely to prefer the clinical management profile of ponesimod over those of siponimod, fingolimod, and ozanimod. This information can help inform recommendations for treating RRMS and facilitate shared decision making between patients and their doctors.

Structure-function relationship of oat flour fractions when blended with wheat flour: Instrumental and nutritional quality characterization of resulting breads.

The present work investigated the structure-function relationship of dry fractionated oat flour (DFOF) as a techno-functional ingredient using bread as a model system. Mechanically, DFOF fractions (F), that is, F1: <224µm, F2: 250-280µm, F3: 280-500µm, F4: 500-600µm, and whole oat flour (F5) were blended with white wheat flour at 10%, 30%, and 50% substitution levels for bread making. The blended flours, doughs, and bread samples were assessed for their techno-functional, nutritional, and structural characteristics. The results of Mixolab and the Rapid Visco Analyzer show that the 50% substituted F3 fraction exhibits the highest water absorption properties (69.53%), whereas the 50% F1 fraction exhibits the highest peak viscosity of the past slurry. Analysis of bread samples revealed a lower particle size of DFOF fractions and higher supplementation levels, increased β-glucan levels (0.13-1.29g/100 bread (db), reduced fermentable monosaccharides, that is, glucose (1.44-0.33g/100g), and fructose (1.06-0.28g/100g). The effect of particle size surpassed the substitution level effect on bread volume reduction. The lowest hardness value for F1 is 10%, and the highest value for F2 is 50%. The total number of cells in the bread slice decreased from the control to the F4 fraction (50%). Multi-criteria analysis indicated that DFOF fractions produced breads with similar structure and higher nutritional value developed from white wheat flour. PRACTICAL APPLICATION: The use of mechanically fractionated oat flours fractions in white wheat flour breads can improve the nutritional profile without affecting the physical properties of the bread product. Based on the oat flour fractions, bakers and food processing companies can tailor the bread formulations for high β-glucan, high fiber, and low reduced sugar claims.

Cropping calendar, agroclimatic and agroecological zoning for rainfed maize (Zea mays L.) under different rainfall scenarios in a semi-arid region of Brazil

Context The productivity of crops is influenced by the available net water balance, which relies on a complex interplay of edaphic and climatic factors. In this sense, rainfall is the leading water input for crop growth and yield, especially in water-scarce regions under semi-arid climates worldwide. Aims This study aimed to define the optimum cropping calendar and the agroclimatic and agroecological zones for rainfed maize in the state of Ceará, which is predominantly located within the Brazilian semi-arid region, assuming different rainfall scenarios. Methods We considered the subdivision of the study area into eight homogeneous precipitation regions according to the regional rainfall pattern. The climatic water balance for each region over two decades was calculated from historical weather data series, assuming three rainy scenarios: dry, regular, and rainy. The agroclimatic zoning was defined through the crop water balance results, soil classification, land use and occupation, slope and temperature, weighted through a multi-criteria decision analysis based on the Analytic Hierarchy Process. Key results The recommended planting period was broader in rainy conditions. However, there may be some dry spells between two 10-day intervals of the calendar, which impair plant growth depending on their intensity. For the dry scenario, the agroclimatic zoning showed that the marginal water deficiency covered 96.55% of the study area. Conclusions Rainfed maize cultivated under the semi-arid climate of Ceará state is viable in rainy conditions, partially restricted in regular years, and not recommended in dry years. Implications This study emphasises the importance of climate monitoring in effective planning for rainfed maize cultivation in semi-arid regions.

EquiCity game: a mathematical serious game for participatory design of spatial configurations

We propose a mathematical framework for developing social-choice games that are designed to mediate decision-making processes for city planning, urban area redevelopment, and architectural configuration of urban housing complexes. The proposed framework features a digital serious gaming approach for participatory design to support transparency and inclusion in the process of decision-making and ensure an equitable balance of sustainable development goals in spatial design outcomes. The mathematical process consists of a Markovian design machine for balancing the design decisions of actors, a massing configurator equipped with fuzzy logic and multi-criteria decision analysis, algebraic graph-theoretical accessibility evaluators, and automated solar-climatic evaluators using geospatial computational geometry. We demonstrate the effectiveness of the framework by implementing a multi-player online game that facilitates a participatory decision-making workshop for forming multi-functional building complexes by providing a generative configurator equipped with automated appraisal/scoring mechanisms for revealing the aggregate impact of alternatives. The EquiCity game empowers a group of decision-makers to reach a fair consensual spatial design by mathematically simulating many rounds of reasonable trade-offs between their decisions, with different levels of interest or control over various types of investments. The novelty of the framework is in its capability to encompass decision-making about the most idiosyncratic aspects of a site related to its heritage status and cultural significance to the most generic aspects such as balancing access to sunlight for the site while respecting ‘the right to sunlight’ of the neighbours of the site, ensuring coherence of the entire configuration with regards to a network of desired closeness ratings, the satisfaction of a programme of requirements, and intricately balancing individual development goals in conjunction with communal goals and environmental design codes.

Automated GIS-based decision tool for rehabilitation of a drinking water infrastructure in Tlemcen, Algeria

Water resource management relies heavily on the utilization of decision-making systems to guide the strategic rehabilitation and renovation of infrastructure within water distribution networks (WDNs). This study aims to develop and apply a scripting tool in ArcGIS for decision-making in WDN. It combines a collection of decision support systems, including Geographic Information Systems (GIS) and multi-criteria analysis, for infrastructure renovation and rehabilitation. The research is divided into two main sections. The first focuses on creating and implementing the analytic hierarchy process tool in ArcGIS, while the second discusses its application in the study area, which is the drinking water distribution network of an urban area in Tlemcen, located in the Northwest of Algeria. The study’s results reveal that 25% of the network is in critical condition and require immediate rehabilitation. Sixty-two percentage of the network is classified as moderately urgent, indicating a pressing but less immediate need for intervention. Finally, the remaining 13% of the network requires attention over a longer timeframe for rehabilitation. The main criteria influencing pipe prioritization are material (26% of total weight), laying date (26% of total weight), and pressure (20% of total weight). This developed tool can be easily adapted and applied by engineers and water management officers. It serves as a guide for decision-makers and planners in urban water management in Tlemcen and can be replicated and applied to other areas worldwide.

The Effects of Climate Change on Streamflow, Nitrogen Loads, and Crop Yields in the Gordes Dam Basin, Turkey

The Mediterranean region is highly vulnerable to climate change. Longer and more intense heatwaves and droughts are expected. The Gordes Dam in Turkey provides drinking water for Izmir city and irrigation water for a wide range of crops grown in the basin. Using the Soil and Water Assessment Tool (SWAT), this study examined the effects of projected climate change (RCP 4.5 and RCP 8.5) on the simulated streamflow, nitrogen loads, and crop yields in the basin for the period of 2031–2060. A hierarchical approach to define the hydrological response units (HRUs) of SWAT and the Fast Automatic Calibration Tool (FACT) were used to reduce computational time and improve model performance. The simulations showed that the average annual discharge into the reservoir is projected to increase by between 0.7 m3/s and 4 m3/s under RCP 4.5 and RCP 8.5 climate change scenarios. The steep slopes and changes in precipitation in the study area may lead to higher simulated streamflow. In addition, the rising temperatures predicted in the projections could lead to earlier spring snowmelt. This could also lead to increased streamflow. Projected nitrogen loads increased by between 8.8 and 25.1 t/year. The results for agricultural production were more variable. While the yields of poppy, tobacco, winter barley, and winter wheat will increase to some extent because of climate change, the yields of maize, cucumbers, and potatoes are all predicted to be negatively affected. Non-continuous and limited data on water quality and crop yields lead to uncertainties, so that the accuracy of the model is affected by these limitations and inconsistencies. However, the results of this study provide a basis for developing sustainable water and land management practices at the catchment scale in response to climate change. The changes in water quality and quantity and the ecological balance resulting from changes in land use and management patterns for economic benefit could not be fully demonstrated in this study. To explore the most appropriate management strategies for sustainable crop production, the SWAT model developed in this study should be further used in a multi-criteria land use optimization analysis that considers not only crop yields but also water quantity and quality targets.

Integrating spatial data and multi-criteria analysis for wind farm suitability mapping in eastern Saudi Arabia

Wind energy offers significant potential for Saudi Arabia's energy future. This framework integrates wind farm suitability analysis with spatially explicit groundwater potential mapping. So, revealing prospective windy sites as optimal zones for wind farm installation has become a vital issue for wind farms in Saudi Arabia's Eastern Province. To power clean energy and groundwater pumping, we deployed a unique blend of multi-criteria decision-making and spatial analysis. Several suitability criteria (17 factors) were used, including wind power density, land cover, and infrastructure, via a two-pronged approach. Five key factors were analyzed through a decision-making process, while the remaining 12 received suitability modeling. The resulting map reveals extensive areas with high wind farm potential. "Very high," "high," and "moderate" suitability zones cover a combined 211,943 ha, compared to a mere 1459 ha with "low" and "very low" potential. Interestingly, "sands" emerged as the surface with the highest concentration of "very high" suitability, while "fallow land" offered the most extensive suitable area overall. Wind power density proved to be the driving force behind these rankings. The study recommends further research to understand how wind power density correlates with wind speed at different altitudes. This could refine wind farm placement and maximize its effectiveness.

Exploring equality and sustainability trade-offs of energy transition outcomes in the United States in 2050

With increasing focus on equitable and just energy transition, it is critical to understand the trade-offs of different decarbonization outcomes across economic, environmental, and social sustainability criteria. In this analysis, we use a multi-criteria decision analysis to quantify sustainability outcomes across 32 decarbonization outcomes in 2050 in the U.S. The economic sustainability criteria we use are system cost, national average retail rate, and electricity system employment. The environmental sustainability criteria we use are life cycle greenhouse gas emissions, life cycle water depletion, life cycle land transformation, and air pollution fatalities. The social sustainability (distributional impacts) criteria we use are retail rate equality across states, electricity employment equality across low-income households, and air pollution disparities across census tracts. We evaluate performance across these criteria under eleven different stakeholder preference scenarios. We find that decarbonization policies with indefinitely extended tax credits have the highest sustainability score under equal criteria weighting, with greater investments in renewable energy technologies, and result in better environmental, system cost, job, and air pollution disparities compared to mid-case scenarios, that only include current policies and CO2 reduction targets. We also see that our multi-criteria decision analysis identifies decarbonization outcomes that would not have been identified as optimal under a single objective, which highlights the importance of trade-off analyses to understand decarbonization outcomes more holistically.

Sustainable mined land reclamation: the pujada nickel case study

Decision making is severely challenging in mined-land reclamation where multiple interests of various and often conflicting stakeholders should be satisfied. Thru the use of Multi-Criteria Analysis (MCA), sustainable options of reclaiming the mined land in manner that is environmentally sound, technically feasible, economically viable, socially acceptable, culturally sensitive and spiritually rooted are fully explored and considered. Multiple stakeholders like; the indigenous peoples, mining host communities, the non-government organization, the church, the mining company, the Mines Bureau, the National Commission on Indigenous Peoples and the local government units were engaged in the study to determine their interests in mining reclamation. Having full appreciation of the stakeholders’ interests and proposed options, the Mine Rehabilitation Fund Committee and the Multi-partite Monitoring Team are confident that reclaiming the mined land thru the options-mix of Forestry and Botanical Park Development shall perform better and is more sustainable. The results of MCDA of the Pujada Nickel Project enabled the decision makers to have confidence that the blended options of Forestry Reclamation Approach (FRA), Sloping Agro-forestry Land Technology (SALT) and Botanical Park Development in transforming the Pujada Nickel Mine shall satisfy the best interests of the multiple mining stakeholders.

Sectorial evaluation and characterization of internal marketing orientation through multicriteria analysis

This research carries out a comparative analysis of the Internal Market Orientation (IMO) to a sample of small and medium enterprise companies, which has been divided into nine groups based on their business sectors. Applying the statistical technique of structural equations, the coefficients of four IMO inputs in each business sector are obtained. Next, the PROMETHEE multicriteria technique is applied to obtain a composite indicator of the IMO implementation of each business sector. The value of the composite indicator together with the GAIA plane allow to distinguish the differences of the IMO profiles, their strengths and their weaknesses. The results show the divergences in the IMO inputs according to the sector, which is evidence that the business sector is a predictor of the IMO implementation of a company.

Driving factors for developing integrated farming: Multi-criteria decision-making analysis

Integrated farming (IF) by temporal and spatial mixing of crops, livestock, fishery, and allied activities in a single farm, is considered a critical multifunctional option for smallholder farmers, who form the backbone of Indian agriculture, to ensure sustainable livelihoods, the productivity of agricultural enterprises, stability of farm income, food and nutritional security. However, the adoption of IF still remains low. To explore the critical factors of IF systems and prioritize them for stakeholders’ decision-making and development of strategies, the current research was undertaken to integrate SWOT (Strengths, Weaknesses, Opportunities, and Threats) - AHP (Analytic Hierarchy Process) analysis. We used a multi-stage sampling to select 60 practicing IF adopters in West Bengal state of eastern India for the collection of pair-wise comparison data on 32 SWOT factors using a close-ended questionnaire and subjected to AHP analysis to understand the quantitative importance of each factor of SWOT. Results of the multi- criteria analysis showed the total priority weight of the opportunity component (0.450) was the highest, followed by strength (0.341), weakness (0.114), and threat components (0.095). Based on the global priority weight of all 32 SWOT factors, sustainable livelihood security” was the key driving factor (0.081) followed by promotion of organic farming (0.072), better risk management (0.063) and incorporation of high-value crops (0.063) of opportunity component. Increased farm production and productivity (0.058) and enhancement in income (0.055) of strength component also played as vital driving factors. There was no factor of weakness and threat components within the first 10 important factors. The insights of this study may help improve extension services to smallholder farmers for prioritizing strategies in the adoption process of IF. Additionally, it can also help policymakers to design targeted policies, remove barriers, foster innovation, and promote sustainable practices, contributing to food security and environmental sustainability.

Multicriteria analysis of the components of ecological paving stones made from plastic and glass waste, and granular reinforcements

The use of plastic waste as a resource in construction applications is an opportunity for environmental protection, conservation of natural resources and reduction of pollution. Unfortunately, they don't always withstand the stresses to which they are subjected, leading to subsidence and collapsing. An analysis of the causes using the Pareto curve shows that 74.47 % of the causes of this collapse are due to poorly formulated mixes and poor choice of raw materials for the composite. The compressive test carried out on the first sample of pavers studied showed a maximum compressive strength value of 4.6 MPa, which is below the standard requirements. As a result, the pavers were considered unsuitable for use on a T5 road. Through the use of the SUPERDECISION software, we were able to identify two favourable constituent materials - glass/glass waste and gravel - for the production of composite paving stones. By adding low-density plastic waste, collected, cleaned and crushed in the form of aggregates, we obtain a compressive strength of 7 MPa with gravel and 8 MPa with glass waste. These values are below the recommendations of the NF EN 1339 standard (Rc ≥ 20 MPa) for T5 traffic. The best composition for ecological paving is therefore (PET/PP/PEBD) + sand + glass (50/12.5/37.5). Analyzing these results shows that the raw materials used for ecological paving should be adapted to the loads.

Combustion and mechanical properties of pellets from biomass and industrial waste

Experimental research findings are reported on the impact of industrial waste additives on the mechanical properties of pellets, their ignition and combustion. The compositions under study consisted of wood sawdust with coal slime/peat/a mixture of straw and rice husk. Composite pellets exhibited high moisture resistance and durability when subjected to vibration. The respective coefficients were 6–32 % higher than for sawdust without additives. The ignition characteristics of wood pellets tended to worsen when additional components were used in their composition. The ignition delay times increased by a factor of 3–4. In most cases, the use of additives increased the combustion duration of pellet fuels. The greatest environmental benefits in terms of carbon oxides were gained from mixtures of straw with rice husk and coal slime. СО2 and СО emissions decreased by 10–20 % and 10–54 %, respectively. A high nitrogen content in peat, coal slime and straw led to 5–94 % higher emissions of NOx for composite pellets. Using plant biomass and peat reduced the concentrations of sulfur oxides almost 3-fold. The results of multi-criteria analysis covering 13 energy, operational, economic and environmental components suggest that the difference in the relative efficiency indicator of wood pellets and compositions with industrial waste additives is 4.4–6.5 %.

Durability evaluation and lifetime prediction of recycled coarse aggregate self-compacting concrete after freeze-thaw and sulfate erosion coupling

This paper aims to study the durability of recycled coarse aggregate self-compacting concrete (RCASCC) after being subjected to freeze-thaw and sulfate coupling. The durability comprehensive evaluation index of RCASCC based on the entropy weight method was defined, and the variation law of the durability comprehensive evaluation index concerning RCA substitution rate, freeze-thaw environment, and coupling frequency was obtained. GM (1, 1) model based on grey system theory was used to evaluate the durability of RCASCC under the coupling effects of freeze-thaw and sulfate attack. The results show that there are some differences in the accuracy of the four GM (1, 1) models. It is recommended that the EGM model can be used to predict the durability of the RCASCC under the coupled effects of freeze-thaw and sulfate erosion. Moreover, the working life of RCASCC under the coupling effects in the outdoor environments of northeast, north, and northwest China was calculated, when the comprehensive evaluation index of durability decreases to 75% as the failure criterion. A multi-criteria analysis employing TOPSIS and VIKOR methods was conducted to evaluate the durability of RCASCC under these coupling effects. A multi criteria analysis was conducted on the durability of RCASCC under the coupling effects of freeze-thaw and sulfate erosion using TOPSIS and VIKOR methods. Under these two rankings, the splitting tensile strength is the index that changes the most after coupling effects, while the compressive strength changes relatively little. The importance of dynamic elastic modulus and weight is different due to different materials and evaluation methods. RC100-H typically exhibits the largest variation, while NC-H and RC50-NM typically exhibit smaller variations.

Urban Growth Modeling in Kurunegala, Sri Lanka using Cellular Automata/Markov Chain Multi-criteria Analysis and Markov-Markovian Transition Estimator

With accelerated global urbanization, the expansion of cities has become a pressing concern for urban planners and researchers. The growth and dynamics of urban encroachment are closely tied to changes in land use, especially in urbanized areas. This study seeks to evaluate the accuracy of the CA-Markov (Cellular Automata) model in predicting land use/land cover changes (LULCC) in the Kurunegala district, Sri Lanka as a result of urban expansion. The investigation employs secondary data, including 2007, 2012, 2017, and 2022 Landsat 05, 07, 08, and 09 images respectively. Using software applications such as ArcGIS 10.8, IDRISI 17.0, and MS-Excel 2019, diverse techniques including supervised classification, Markovian transition estimation, and CAMarkov chain analysis, this study attempts to analyze the Urban Growth Modeling for 2027 and 2037 using CA-Markov Chain Multi-criteria Analysis (MCA) under Markov-Markovian Transition Estimator. The study used 32 spatial variables for determining the LULCC. As per the derived results, from 2022 to 2027, urban areas have increased quite markedly. The vegetation cover area has reduced and the areas of water bodies have increased spatially. From 2027 to 2037, the urban area increment is 72.552%. Also, vegetation cover and water body distribution have reduced by 8.051% and 39.91% respectively.

GIS-based multi-criteria analysis for solar, wind, and biomass energy potential: A case study of Iraq with implications for climate goals

The study utilizes a GIS-Based Multi-Criteria Analysis to evaluate the viability of solar, wind, and biomass energy in Iraq, focusing on enhancing the nation's energy independence and meeting international climate objectives. Detailed spatial analysis revealed specific zones suited for the efficient installation of energy power plants. Zones with an energy surplus factor of less than 0.2 are deemed not viable for development, whereas regions with factors less than 0.4 are ideal for harnessing solar, wind, and biomass resources. Furthermore, zones with surplus factors greater than 0.6 are highly recommended for energy projects. Notably, the results show that strategic development of these zones can cater to between 45 % and 68 % of the country total energy demand, potentially reducing the CO2 footprint by 0.5. Moreover, with an increase in the construction threshold, the CO2 reduction potential has shown a decrease to 1.29E+08 tones, particularly evident in areas with rigorous construction standards. A plateau in reduction figures is observed once the construction threshold surpasses 3.5, stabilizing between 2.5E+07 tones. As the threshold exceeds 5, a further stabilization is noted, consistently around 2.17E+07 tones, persisting even when the threshold approaches 8. The outcomes underscores the critical role of strategic zoning in maximizing renewable energy potential, highlighting pathways for the country to achieve energy self-sufficiency and make significant strides in climate goals.