Cost Estimation System Research Articles

Shared mooring system designs and cost estimates for wave energy arrays

For floating renewable energy devices to become more cost-efficient and commercially scalable, their mooring system designs must be low-cost and suited for large-scale installations. Large arrays of floating devices, such as wave energy converters (WECs), will likely be designed with an individual mooring system for each device in the array. However, new mooring technology advancements provide options to use shared mooring lines to connect adjacent devices to one another, reducing the total number of anchors in the array, thereby reducing material use and cost. This paper explores the design, modeling, and cost analysis of shared mooring systems for various sizes of arrays consisting of heaving oscillating water column (OWC) WECs. Shared mooring systems for WEC arrays sized in 2×N and N×N grid layouts are designed to meet the relevant design standards, checking their performance with a nonlinear time-domain dynamic simulation, and the costs of each are calculated and compared. Several assumptions are taken in the design process to produce efficient results, providing a preliminary optimization for guidance on design decisions rather than a full, detailed design analysis. Mooring system costs per WEC were found to decrease as the number of WECs in the array increase, up to certain array sizes. The 2 × 3 array had the lowest mooring system cost per WEC out of all arrays considered, with a 60% cost reduction relative to using individual mooring systems. The 3 × 3 and 4 × 4 arrays achieved a 50% cost per WEC reduction. In addition to these significant cost reductions, the shared mooring system designs can provide advantages through smaller mooring system footprints, lower installation times, and less seabed disturbance.

Developing preliminary cost estimates for foundation systems of high-rise buildings

This study provided a unique Artificial intelligence (AI) model for the cost estimation of the foundation system for high-rise buildings. First, parametric data research was conducted, including 180 examples of foundation systems for high-rise building models related to criteria such as average column spacing, floor height, slap load, overall weight, base shear, and over. In addition, moment, gravity load, seismic load, design load, various columns (mid-edge-corner), soil profile, bearing capacity, GWT, excavation depth, and foundation systems are all factors to consider (shallow and deep footing). The research encompassed column spacing (5.0, 7.0, and 9.0 m) and the number of stories from 15 to 35, with an average cost decrease of 15%. The AI model utilizes extensive machine learning algorithms to analyze structural and geotechnical parameters. It provides a predictive tool that improves decision-making in the preliminary design. The methodology includes collecting data, training models utilizing innovative neural network techniques and validating them against current cost estimation models. The findings indicate that the AI model significantly improves the accuracy of cost estimations, with a precision rate of 95%, compared to traditional methods. Moreover, the model presents a potential cost savings of up to 15%. Construction designers and decision-makers may utilize the study’s findings to increase the accuracy of foundation system selection, lower costs and construction length, and improve overall project performance. Future work may involve applying this concept to infrastructure and substructure projects and collecting more data for benchmarking and empirical study.

Photo-thermal activation of persulfate for the efficient degradation of synthetic and real industrial wastewaters: System optimization and cost estimation

The photo-thermal activation of persulfate (PS) was carried out to degrade various pollutants such as reactive blue-222 (RB-222) dye, sulfamethazine, and atrazine. Optimizing the operating parameters showed that using 0.90 g/L of PS at pH 7, temperature of 90 °C, initial dye concentration of 21.60 mg/L, and reaction time of 120 min could attain a removal efficiency of 99.30%. The degradation mechanism was explored indicating that hydroxyl and sulfate radicals were the prevailing reactive species. The degradation percentages of 10 mg/L of sulfamethazine and atrazine were 83.30% and 70.60%, respectively, whereas the mineralization ratio was 63.50% in the case of real textile wastewater under the optimal conditions at a reaction time of 120 min. The treatment cost per 1 m3 of real wastewater was appraised to be 1.13 $/m3 which assured the inexpensiveness of the proposed treatment system. This study presents an effective and low-cost treatment system that can be implemented on an industrial scale.

Design and Dynamic Analysis of a Co-Existence Solution Between a Semi-Submersible Offshore Fish Cage and a Spar-Type Floating Offshore Wind Turbine

Abstract Clean energy captured by offshore wind turbines has been widely used for supporting onshore activities. In the near future, facilities such as offshore wind turbines can also play an important role in the energy transition of offshore activities. Offshore wind energy can be employed for electrifying operations in offshore fish farms, which are traditionally supplied by diesel-engine barges/generators. Based on this motivation, this study focuses on the design of a shared mooring system between a semi-submersible offshore fish cage and a spar-type floating wind turbine. A numerical model of the proposed shared mooring system is implemented in a global response analysis software sima for performing fully coupled time-domain simulations. The configuration of the shared mooring line is determined using an engineering approach, which comprises Irvine’s formulation, system eigenvalue analysis, and cost estimation. Moreover, relevant case studies by altering the environmental conditions are performed. Extreme operational conditions that may give large relative motions are investigated thoroughly. The dynamic performance of the integrated system is compared with that of individual structures. The global motion of the floating wind turbine and its mooring line’s tension behavior are obviously influenced by the existence of the shared line. In general, the present work investigates the feasibility of a shared mooring system for these types of offshore structures and further gives insights into the engineering design procedure.

CES: Cost Estimation System for Enhancing the Processing of Car Insurance Claims

CES: Cost Estimation System for Enhancing the Processing of Car Insurance Claims

ГОСУДАРСТВЕННОЕ РЕГУЛИРОВАНИЕ ПРОЦЕССОВ ЦИФРОВОЙ ТРАНСФОРМАЦИИ ЭКОНОМИЧЕСКОЙ ДЕЯТЕЛЬНОСТИ В СФЕРЕ ПРОЕКТИРОВАНИЯ

This article features basic digital economics state policy. It covers consequences of economics digital modelling in terms of capital construction projects. The article reveals current level of digital maturity of design processes and its relationship with related areas of economic activity. Particular attention is paid to the integration of the cost estimate system into information modeling processes. Based on the results of the design processes maturity analysis, proposals were formulated on further directions for state regulation of digital transformation.

Digital transformation for cost estimation system via meta-learning and an empirical study in aerospace industry

It is increasingly challenging to estimate product cost to optimize the quotation decision for aerospace manufacturing companies owing to the diversity of designations, intermittent demands, complicated decision procedure between different functional departments, and knowledge gaps among the involved decision makers. There is a need of effective solutions to support digital transformation of manual approach in which it can expedite and enhance the accuracy of cost estimation by automating specific tasks and streamlining decision processes. Although a number of studies have been done to enhance the performance of forecasting models, little research has been done to address the interrelations between cost estimation model and the associated decisions for quotation. Focusing on realistic needs, this study aims to develop a digital cost estimation system by integrating data-driven methodologies, search engines, and rule-based decision mechanism based on domain knowledge for improving the accuracy of cost estimation and the effectiveness of quotation for revenue management. An empirical study was conducted in a global aerospace manufacturer in Taiwan for validation. The results have shown the practical viability for the proposed framework with better performance than conventional approaches. The developed solution has been implemented.

Integrated design of a bus-bike system considering realistic route options and bike availability

This paper examines the design of a transit system that integrates a fixed-route bus service and a bike-sharing service. Bike availability – the average probability that a traveller can find a bike at a dock – is modelled as an analytical function of bike utilization rate, which depends on travel demand, bike usage and bike fleet size. The proposed system also recognizes the greater flexibility provided by biking. Specifically, a traveller can choose between the closest bus stop and a more distant stop for access, egress or both. Whether the closest stop is a better choice depends on the relative position of the traveller’s origin and destination, as well as system design parameters. This interdependence complicates the estimation of average system cost, which is conditional on route choice. Using a stylized analysis approach, we construct the optimal design problem as a mixed integer programme with a small number of decision variables. Results from our numerical experiments show the integrated bus-bike system promises a modest but consistent improvement over several benchmark systems, especially in poorer cities with lower demand density. We find a large share of travellers, more than 20% in nearly all cases tested, opt not to use the nearest bus stop in an optimally designed system. The system also tends to maintain a high level of bike availability: the probability of finding a bike rarely drops below 90% except in very poor cities.

Review of Thermal Management Technology for Electric Vehicles

The burgeoning electric vehicle industry has become a crucial player in tackling environmental pollution and addressing oil scarcity. As these vehicles continue to advance, effective thermal management systems are essential to ensure battery safety, optimize energy utilization, and prolong vehicle lifespan. This paper presents an exhaustive review of diverse thermal management approaches at both the component and system levels, focusing on electric vehicle air conditioning systems, battery thermal management systems, and motor thermal management systems. In each subsystem, an advanced heat transfer process with phase change is recommended to dissipate the heat or directly cool the target. Moreover, the review suggested that a comprehensive integration of AC systems, battery thermal management systems, and motor thermal management systems is inevitable and is expected to maximize energy utilization efficiency. The challenges and limitations of existing thermal management systems, including system integration, control algorithms, performance balance, and cost estimation, are discussed, along with potential avenues for future research. This paper is expected to serve as a valuable reference for forthcoming research.

Design, scaling and cost evaluations of circulating fluidized‐bed systems for biomass pyrolysis

AbstractTo generate updated and transparent capital cost estimates for biomass fast pyrolysis equipment, refinery fluidized catalytic cracking design and sizing principles are examined and extended to pyrolysis of woody biomass. Capital costs for the sized equipment are estimated with process‐industry software. A one‐dimensional flow simulation with pyrolysis kinetics is leveraged to validate the fluidization conditions and thermal energy balance. After successful sizing and a system cost estimate of $2.8 M (in 2016 US$) at the biorefinery scale of 1000 metric tons per day (MTD), these methods were exercised for even smaller equipment at the distributed pyrolysis scale with modifications to the process design constraints, and not directly comparable with the 1000 MTD case, arriving at capital cost estimates of $1.2 M for a 500 ton/day system and $0.9 M for a 200 ton/day system. It is noted that this work only estimates purchased equipment costs at the ±50% accuracy level; there are significant other custom factors applicable to each installation based on location, maturity, scale, complexities during installation, engineering and licensing costs, etc. that need to be added on to these estimates to derive investment costs.

Students’ Systems Thinking Competencies Level Identification through Concept Maps Assessment

Systems Thinking Competencies have become extremely important and widely studied due to increasing systems complexity. Because of this, when they are taught, it is extremely useful to identify whether or not students own Systems Thinking Competencies in order to design a specific teaching strategy. This research applied an Adapted Holistic Scoring Method to assess Concept Maps developed by postgraduate and undergraduate engineering students in order to identify Systems Thinking Competencies. It had two phases. At the first one, Students showed an acceptable knowledge of cost estimation drivers, and a certain level of Systems Thinking Competencies. In the second phase, both cost estimation drivers and Systems Thinking Competencies showed an improvement. Mann-Whitney U-test was applied in order to identify if there were significant differences between Phase 1 and Phase 2. Confidence level of 95%, and a significance level of 0.05 was considered.

A Lean Knowledge-Based Decision Support System for Cost Estimation in the Foundry Industry

A Lean Knowledge-Based Decision Support System for Cost Estimation in the Foundry Industry

방산원가관리체계 개선을 위한 인공지능(AI) 기반의 RPA 적용방안 개념연구

This study proposes three methodologies to improve the Defense Cost Management System through the application of RPA(Robotic Process Automation). This expects to improve the continuity, accuracy, and efficiency of cost estimation. First, an RPA-based cost estimation system is established. An AI(Artificial Intelligence) implemented RPA system performs validation of cost data and simple repetitive tasks, and thus, it prevents the errors and increases the efficiency in associated tasks. Second, an integrated operation of cost and cost-management is performed. Through this, the issues caused by database separation and key-value differences between the ‘Defense Integrated Cost System’, which manages cost tasks, and the ‘Defense Standards Comprehensive Information System’, which manages defense standards and standardization tasks, can be improved. Finally, a feedback system for cost analysis and cost information is established. This standardizes technologies and associated costs in the weapon acquisition phases. In addition, it collects, stores, and manages cost analysis and estimation records regularly, and makes it possible to reuse the information when a new weapon system requirement arises.

Soft Hunting Algorithm for Auto-Tuning Software Reliability Growth Models

Nature-inspired algorithms are popular for auto-tuning software reliability growth models in recent decades due to their derivative-free natural tendency to circumvent the local optima problem. These methods have indeed exhibited enormous effectiveness in estimating software dependability. The goal of this study is to present a new nature-inspired approach for parameter improvement of system reliability predictions based on the hunting abilities of smoother-coated otters. The otters’ most notable characteristic is their ability to hunt in groups. In this study, clever otter hunting behavior is used to enhance reliability engineering parameters of the model. Otters work well together and have a strong sense of teamwork. Matte finish coated otters’ smart fish scavenging capacity distinguishes them from many other swarm intelligence-based techniques. Three stages of otter searching are accomplished: traveling in a V formation in the direction of the prey’s movements, advancing forcefully via the stream, and then assaulting the prey on the beach. Three software dependability models are utilized to validate the applicability of the suggested approach. The study’s findings demonstrate that the suggested algorithm outperformed the ABC, GA, and PSO algorithms by 75% and 50%, respectively, in terms of reduced SSE and lower MSE. The smooth-coated otter’s cognitive foraging behavior gives great gain capabilities in parameters software cost estimation system reliability analysis. The outcomes are encouraging for auto-tuning software reliability growth models. Smooth-covered otter optimization can also be used to solve other efficiency challenges.

Cost estimates for modern e-business systems

Recently, the adoption of cloud computing for e-business has become standardized and began evolving into further execution models, such as serverless computing. One of the features of cloud computing is to provide computational resources on a pay-as-you-go model, where users pay only for what they use. These managed and serviced resources have characteristics that make them suitable for cost estimation in the early stages of business. This paper proposes a rapid cost estimation method for serverless computing using directed acyclic graph- (DAG) based formalization and matrix operations. Using a case study, we demonstrate that cost estimation under serverless computing can be effective in the early stages of business. Furthermore, we show that the cost estimation of serverless computing is more proportional to the required computational resources than the virtual machine- (VM) based cost estimation method.

A photo-assisted electrochemical-based demonstrator for green ammonia synthesis

Bridging laboratory research and practical utilization is of crucial importance for the development of green ammonia synthetic technologies. A decentralized photo-assisted electrochemical-based demonstrator has been proposed for green ammonia synthesis from renewable electricity, air and water, where well-known defect-laden WO3 is used as the working electrode, and a commercially available PV panel supplies renewable electricity. In this demonstrator, defect-laden WO3 exhibits the optimum electrochemical NH3 formation rate (4.51 × 10–12 mol s−1 cm−2) in 0.1 M K2SO4 in a photovoltaic electrochemical (PV-EC) system. A system-level energy and cost analysis was conducted to investigate its economic viability and a general evaluation tool for system performance and cost estimation was proposed. This advance enables the possibility of integrating the small-scale green ammonia demonstrator into a stand-alone farm system.

A multi-perspective approach to support collaborative cost management in supplier-buyer dyads

Joint cost management is a decisive factor for sustainable collaboration in supplier-buyer dyads. For both parties the establishment of an accurate cost estimation (CE) framework supports managing suppliers' costs as well as manufacturer's quotation costing. Grounded on resource dependence theory and following a design science research approach, this study introduces a multi-perspective CE system inspired by statistical learning, deep learning, decision making, and multi-agent theory. We evaluate our system by a single case and computer simulation study, using empirical data coming from observations and archives at a large Bavarian original equipment manufacturer (OEM). The results indicate that our CE approach allows to select the most significant cost-drivers and predict total costs of parts and assemblies with high accuracy. This supports the supplier in efficiently managing its costs. In making the CE blackbox model transparent using a combination of model agnostic post-hoc explainable artificial intelligence approaches we foster user acceptance for both suppliers and OEMs. All CE artifacts are ensembled in a multi-agent system to automatically manage costs with suppliers and furthermore, as a model extension, can lead to a collaborative price agreement. Our system supports supply chain managers on both sides in entering into a sustainable long partnership.

A Cost Modelling System for Recycling Carbon Fiber-Reinforced Composites.

Cost-effective and environmentally responsible ways of carbon fiber-reinforced composite (CFRP) recycling are increasingly important, owing to the rapidly increasing use of these materials in many industries such as the aerospace, automotive and energy sectors. Product designers need to consider the costs associated with manufacturing and the end-of-life stage of such materials to make informed decisions. They also need to understand the current methods of composite recycling and disposal and their impact on the end-of-life costs. A comprehensive literature review indicated that there is no such tool to estimate CFRP recycling costs without any prior knowledge and expertise. Therefore, this research paper proposed a novel knowledge-based system for the cost modelling of recycling CFRP that does not require in-depth knowledge from a user. A prototype of a cost estimation system has been developed based on existing CFRP recycling techniques such as mechanical recycling, pyrolysis, fluidized bed, and supercritical water. The proposed system has the ability to select the appropriate recycling techniques based on a user’s needs with the help of an optimization module based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Estimating recycling costs has taken into consideration various factors such as different material types in different industries, transportation, and dismantling costs. The developed system can be employed to support early-stage designers and decision-making stakeholders in terms of understanding and predicting recycling costs easily and quickly.

Application of Project Whole Process Cost Control in Construction Project Cost Audit

This paper summarizes the theory of project cost, which paves the way for the basic theoretical system of construction project cost estimation. This paper expounds the function of project cost and the main factors affecting project cost. Secondly, the basic principles of BP neural network method and grey theory are described, which provides technical support for the establishment of construction cost estimation system model. In view of the shortcomings of BP neural network, such as slow convergence speed, easy to fall into local minimum and inaccurate prediction, this paper proposes an improved method to process the data of BP neural network input layer with grey one-time accumulation, and then use grey one-time subtraction to process the output layer. Finally, the optimization model based on grey BP neural network method is established to establish a more accurate knowledge framework system in order to solve the construction cost estimation.

MAPPAJA’ PRACTICES IN AGRICULTURAL COMMODITY TRADING IN THE DISTRICT OF WEST SINJAI, SINJAI REGENCY

This study will elaborate on the form of mappaja' trading, which is considered as an attractive economic issue as in its transactions, people do not use a system of weighing scales in trading their harvests, but with a cost estimation system for the goods. Therefore, in the trading practice, there is often a discrepancy between the harvest and the buyer’s expectation, because it may contain an element of gharar/obscurity of the goods, which can lead to an invalid transaction and harm one of the parties. This study indicated that the practice of mappaja' for agricultural commodities has occurred for a long time. The mechanism is by estimating the number of plants based on mutual trust and responsibility. The agricultural commodities used as the mappaja' objects are cloves and vegetables (carrots, cabbage, and tomatoes). The payment method in mappaja' practice is carried out in two ways, namely full payment and twice payment. Twice payment refers to the transaction where half of the payment was handed over on the agreement as a down payment and a sign of completion, then the rest of the payment were handed after the harvest. The condition of the plant is ready to harvest or not ready for harvest in the transaction of mappaja’. The rights and obligations of both parties are that traders are obliged to make payments to farmers according to the agreement and for the farmers, they have to keep taking good care of the plants if at the time of the transaction the condition of the plants is still not ready for harvest.