Detailed Design Stage Research Articles

A model utilizing the artificial neural network in cost estimation of construction projects in Jordan

PurposeCost estimation is one of the most significant steps in construction planning, which must be undertaken in the preliminary stages of any project; it is required for all projects to establish the project's budget. Confidence in these initial estimates is low, primarily due to the limited availability of suitable data, which leads the construction projects to frequently end up over budget. This paper investigated the efficacy of artificial neural networks (ANNs) methodologies in overcoming cost estimation problems in the early phases of the building design process.Design/methodology/approachCost and design data from 104 projects constructed over the past five years in Jordan were used to develop, train and test ANN models. At the detailed design stage, 53 design factors were utilized to develop the first ANN model; then the factors were reduced to 41 and were utilized to develop the second predictive model at the schematic design stage. Finally, 27 design factors available at the concept design stage were utilized for the third ANN model.FindingsThe models achieved average cost estimation accuracy of 98, 98 and 97% in the detailed, schematic and concept design stages, respectively.Research limitations/implicationsThis paper formulated the aims and objectives to be applicable only in Jordan using historical data of building projects.Originality/valueThe ANN approach introduced as a management tool is expected to provide the stakeholders in the engineering business with an indispensable tool for predicting the cost with limited data at the early stages of construction projects.

From sketch BIM to design BIM: An element identification approach using Industry Foundation Classes and object recognition

Building Information Modelling (BIM) is a promising technology for building lifecycle management. Currently, BIM has been extensively used in both the sketch design (sketch) and detailed design (design) stages. Due to different purposes and different BIM tools, the reusability of sketch BIM models in the design stage is still challenging. To address this issue, this study proposes a building element identification scheme using a segmentation-aggregation strategy, termed EI-SA. Since Industry Foundation Classes (IFC) is the international standard of BIM, the EI-SA is built according to the IFC specification. Firstly, the element identification Problem is formally defined, followed by the overall framework of the EI-SA. Then, a presentation-level BIM segmentation algorithm is developed to divide a sketch BIM model into slices of geometric representations. Thirdly, a representation aggregation scheme is proposed to solve the element identification problem. The representation aggregation scheme employs a triangle-triangle intersection to detect the geometric connection and an object recognition algorithm to identify elements. Finally, experiments were conducted on several sketch BIM models. The experiment results showed that the EI-SA identified 82.22% elements on average, which verified the effectiveness of the EI-SA. To the best of our knowledge, this study is the first to solve the building element identification problem according to IFC. The proposed EI-SA will bridge the gap between sketch BIM models and design BIM models, smooth the reusability of data from the sketch stage to downstream stages, and improve the design efficiency by avoiding the re-designing of building elements.

Neutronics influence of poloidal nonuniform neutron wall loading on helium-cooled ceramic breeder blanket for CFETR

Abstract After its conceptual design, the Chinese Fusion Engineering Test Reactor (CFETR) is now at the stage of detailed engineering design. During this stage, many detailed factors should be considered for the components in the CFETR. In this paper, the neutronics influence of poloidal nonuniform neutron wall loading (NWL) is studied for helium-cooled ceramic breeder (HCCB) blanket of the CFETR. The blanket is divided into five parts along the poloidal direction. Each part is composed of the armor, the first wall, tritium breeders, neutron multipliers, and the manifold in the flow distribution zone. The nuclear heat deposition and the tritium breeding performance of the CFETR HCCB blanket are studied with symmetrical and stepped NWL distributions. The results obtained from the uniform NWL distribution are also presented as the reference. For each NWL distribution, the nuclear heat deposition and the tritium breeding capability in different blanket parts are compared. The results show that the nonuniform NWL distribution has almost no influence on the total nuclear heat deposition or the total tritium production. The overall variation is less than 1 ‰ compared to the results under the uniform NWL distribution. However, the local performances of different blanket parts are affected obviously. The maximum variation is over 20 %, which should be focused on during the design for the flow distribution of helium coolant and purge gas. The present work aims to provide an important guidance for the detailed design and structural optimization of the blanket for the CFETR, especially for consideration of the high-level fusion power during phase II (over 1 GW).

Magnet design for Iranian Light Source Facility storage ring

The Iranian Light Source Facility (ILSF) is a 3 GeV synchrotron radiation laboratory which is in the detailed design stage and the main building site is being excavated in Qazvin, 150 km from Tehran. The ILSF storage ring (SR) is based on a Five-Bend Achromat (5BA) lattice providing an ultra-low beam emittance of 270 pm rad. The ring is comprised of 100 combined dipole magnets, 240 quadrupoles and 320 sextupoles with additional coils as dipole and skew quadrupole correctors. In this paper, some design features of the SR magnets along with their detailed physical design are debated. The corresponding electrical and cooling calculations and mechanical layouts are investigated as well.

Diverse discrete material optimization for multi-patch laminates under vibration environment

In practical engineering, the design scheme is generally a compromise solution that meets various requirements. In most cases, the traditional optimization method provides a single optimized solution, which may be prone to fail during the subsequent design stage because some unpredictable requirements may be not considered in the preliminary optimization process. For example, maximizing fundamental frequency is generally regarded as the optimization objective for aerospace structures under the vibration environment in the preliminary design stage. However, the optimized solution may fail for strength, buckling, or other requirements during the subsequent detailed design stage. Therefore, it is crucial to provide multiple alternative solutions for insurance. In this paper, a diverse discrete material optimization (DDMO) framework is proposed for multi-patch laminates. It can optimize the material topology layout and fiber orientations of composite structures simultaneously and provide multiple alternative solutions that have diversity in design space and different potential performance. In this paper, a diversity index for discrete variables is proposed and the discrete material optimization (DMO) method with the diversity index constraint is employed to perform the DDMO. Two illustrative examples are used to verify the effectiveness of the proposed optimization framework, including a simple example of a composite plate and a complex engineering example of an S-shaped curved shell. Results indicate that, the proposed method can provide multiple diverse alternative solutions with similar performance in the optimization objective, which are verified to have better potential performance than the single solution by the traditional single design method. Moreover, multiple design options by the diverse optimization method can contribute to reducing the probability of redesign and shortening the design cycle.

Practical Energy Retrofit of Heat Exchanger Network Not Containing Utility Path

The paper presents a method developed for the energy retrofit of specific Heat Exchanger Networks not containing Utility Paths. This useful and highly practically oriented method involves a systematic approach to obtaining the most efficient minimal modification topology of a Heat Exchanger Network, which brings the greatest benefits in terms of energy savings of the modified process. In principle, it is focused on finding the most suitable location for a new heat exchanger insertion to create the most efficient Utility Path. The next step of the developed retrofit method is the detailed design of the newly integrated heat exchanger using commercial software in combination with several heuristic rules regarding the cost-free investment and maintenance cost minimization of a new heat exchanger and considering heat transfer enhancement within the available exchanger type, space, and fluids pressure drop constraints. The detail design stage of the method also includes observation and reassessment of the performance and operational parameters of the existing heat exchangers. Then, the developed method is applied to the case of the Heat Exchanger Network retrofit in the process of the hydrogenation of oil.

Critical success factors for management of the early stages of prefabricated prefinished volumetric construction project life cycle

PurposeFor many types of buildings, prefabricated prefinished volumetric construction (PPVC) is increasingly becoming a preferred alternative construction approach. Empirical evidence of project performance has consistently demonstrated that the ultimate success of PPVC projects is directly linked to the key decisions made at the outset of the PPVC project life cycle. However, there is limited knowledge of how to successfully manage these early stages. This research identified and evaluated the critical success factors (CSFs) required for the management of the conception, planning and design stages of the PPVC project life cycle.Design/methodology/approachA multistage methodological framework was adopted to identify and evaluate the CSFs for management of the early stages of the PPVC project life cycle. Based on a comprehensive literature review and expert review, a list of the 9 CSFs relevant to the early stages of the PPVC project life cycle was established. Drawing on an online-based international questionnaire survey with global PPVC experts, the CSFs were measured. The data set was statistically tested for reliability and analyzed using several techniques such as mean scores, relativity weightings and significance analysis.FindingsThe analysis revealed that the top 5 most influential CSFs for management of the early stages of the PPVC project life cycle include robust design specifications, accurate drawings and early design freeze; good working collaboration, effective communication and information sharing among project participants; effective stakeholder management; extensive project planning and scheduling; and early engagement of key players. The research further found correlations among the CSFs and proposed a conceptual framework for the management of the early stages of the PPVC project life cycle.Research limitations/implicationsThe research recognizes that data quality and reliability risks are the major drawbacks of online questionnaire surveys but the engagement of experts with substantial theoretical and hands-on experiences in PPVC projects helped to minimize these risks. Although small, the sample size was justified and compared with studies that adopted the same data collection approach but analyzed even smaller samples. However, the results should be interpreted against these limitations.Practical implicationsThe findings suggest that effective management of the early stages of the PPVC project lifecycle requires early commitment to the PPVC approach in a project; detailed planning and assessment of the suitability of PPVC for the given project; and collaborative design with manufacturers and suppliers to address module production challenges at the detailed design stage. These findings practically instructive and may serve as management support during PPVC implementation.Originality/valueThis research constitutes the first exclusive attempt at identifying the CSFs for successful management of the early stages of the PPVC project life cycle. It provides a fresh and more in-depth understanding of how best to manage the early stages of the PPVC project life cycle. Thus, it contributes to the practice and praxis of the PPVC project implementation discourse.

Data-driven product design toward intelligent manufacturing: A review

With the arrival of the big data era, a lot of valuable data have been generated in the entire product life cycle. The gathered product data contain a lot of design knowledge, which brings new opportunities to enhance the production efficiency and product competitiveness. Data-driven product design is an effective and popular design method, which can provide sufficient support for designers to make smart decisions. This article focuses on a comprehensive review of the existing research in data-driven product design. Based on the product design process, this article summarizes the data-driven design methods into the following aspects: customer requirement analysis, conceptual design, detailed design, and design knowledge support tools. In the customer requirement analysis stage, through data mining and transformation methods, customer requirements are predicted and then mapped to obtain accurate requirement expressions for aiding designers to explore the design space. In the conceptual design stage, the intelligent algorithms and data warehouse technologies are discussed in detail for function reasoning and scheme decision-making to achieve the iterative mapping from customer space to solution space. In the detailed design stage, data modeling languages and methods are introduced to support the simulation verification of the design process. For the design knowledge support tools, the methods of extracting knowledge from product data are discussed in detail, and the realization of computer-aided conceptual design is assisted through the development of knowledge-oriented design tools. Finally, this article summarizes the key points of data-driven product design research and provides an outlook for future research directions.

Research on Graphic User Interface Automation Testing Technology Based on Cloud Platform

As the soul of computer, software has more and more important influence on human beings. GUI (Graphical User Interface) technology is widely used because of its friendly interface and easy operation. It is an important part of software nowadays. No matter what kind of software, from requirement analysis to detailed code design stage, we need to use excellent testing technology to lay the foundation for the smooth development of software. Software testing technology has become an important branch affecting the development of software industry. Especially in the regression test conducted in the later stage of the test, it is necessary to verify whether the previously discovered problem is solved in the new version. Automating software testing can make a large number of tests programmatically repeated. Not only does it save a lot of labor, but it also improves test efficiency and guarantees the quality of the test. This paper proposes a graphical user interface automation test technology for cloud platforms, which provides assurance for testers to easily create and flexibly maintain test code.

Total Site Heat Integration Considering Optimum Pressure Drops

In this study, a new methodology is developed for Total Site Minimum Energy Requirement (MER) targeting, in which optimum stream pressure drops ((Ps) are considered for each individual process. To validate the accuracy of the methodology, two Total Site (TS) systems comprising processes A and B and processes C and D are selected and evaluated using two different approaches; I) considering streams’ assumed heat transfer coefficient (conventional method) and II) considering streams’ allowable (Ps. In the second approach, the possibility of pumps/compressors replacement is first investigated for each individual process, through exploring a 3-way trade-off between energy consumption, area requirement and hydraulic system. The resulting data are then used to construct a Total Site profiles (TSPs) for MER targeting. These profiles depict that the hot and cold utility values, when (Ps are optimized, are much less than those obtained in conventional method using assumed coefficients. Moreover, the TS energy targets that are estimated in this method are more realistic and compatible with the results of detailed design stage.

Aerodynamic Analysis of a Quadcopter Drone Propeller with the Use of Computational Fluid Dynamics

In the current work, an analysis for the initial aerodynamic assessment of a small sized quadcopter drone propeller is presented, focusing on the drone aerodynamic characteristics optimization. The objective of the work is to design and construct from scratch a quadcopter drone, in order to participate to the UAS Challenge 2020 student competition (www.imeche.org/events/challenges/uas-challenge). The study of the quadcopter design and construction is carried out by the Democritus Aeronautical Rescue Team (DART), a team that consists of students of the Democritus University of Thrace School of Engineering. The performance analysis which is presented is mainly based on the aerodynamic characterization of an initial selected propeller design, which will be used for the examined quadcopter, with the use of Computational Fluid Dynamics (CFD). Three turbulence models were selected for the computations each one based on a different modelling approach. The computations are assessed and conclusions regarding the propeller design are derived. Based on the computations, the optimal propeller shape will be designed, and the results will further help to the refinement of the overall quadcopter aerodynamic layout in the final detailed design stages for the UAS Challenge competition.

Assessing complex failure scenarios of on-board distributed systems using a Markov chain

ABSTRACTVulnerability reduction is an important topic during the design of naval ships because they are designed to operate in hostile environments and because their on-board distributed systems are becoming increasingly complex. The vulnerability needs to be addressed in the early design stages already, in order to prevent expensive or time-consuming modifications in later, more detailed design stages. However, most existing methods for assessing the vulnerability are better suited for more detailed design stages. Furthermore, existing methods often rely on pre-defined damage scenarios, while damage – or system failure in general – may also occur in ways that were not expected beforehand. This paper proposes a method that addresses these gaps. This is done by incorporating several additions to an existing vulnerability method that has been developed by the authors, using a Markov chain. With this method, there is no longer a need for modelling individual hits or failure scenarios. The additions are illustrated by two test cases. In the first one, a notional Ocean-going Patrol Vessel is considered, and damage is related to physical locations in the ship. The second test case considers a chilled water distribution system in more detail, with failures modelled independent from the physical architecture. The quantitative nature of the results provide an indication of the generic, overall vulnerability of the distributed systems, which is meant to be used in the early design stages for identifying trade-offs and prioritising capabilities.

CAD Of Anticorrosive Protection Of Steel Structures

The choice of cost-effective method of anticorrosive protection of steel structures is an urgent and time consuming task, considering the significant number of protection ways, differing from each other in the complex of technological, physical, chemical and economic characteristics. To reduce the complexity of solving this problem, the author proposes a computational tool that can be considered as a subsystem of computer-aided design and used at the stage of variant and detailed design of steel structures. As a criterion of the effectiveness of the anti-corrosion protection method, the cost of the protective coating during the service life is accepted. The analysis of existing methods of steel protection against corrosion is performed, the possibility of their use for the protection of the most common steel structures is established, as well as the estimated period of effective operation of the coating. The developed computational tool makes it possible to choose the best method of protection of steel structures against corrosion, taking into account the operating conditions of the protected structure and the possibility of using a protective coating.

Macroscale bending large-deformation and microbuckling behavior of a unidirectional fiber-reinforced soft composite

Due to microscale fiber microbuckling, a fiber-reinforced soft composite demonstrates large macroscale bending deformation (e.g. 10% reversible macroscale compressive strain), which is larger than that of a convenient fiber-reinforced plastics (e.g. 1.5–2% elongation/compression at break). To investigate the deformation behavior, a normalized average energy density of a fiber-reinforced soft composite laminate was derived. By using a self-consistent approach according to the minimum energy principle, a series of analytical expressions were derived by a simplified theoretical method through solving simplified partial differential equations of average energy density. Furthermore, an improved numerical calculation method was developed using the full four terms of partial differential equations of average energy density by employing the results of simplified theoretical method as initial calculating values. The dimensionless results demonstrated that the trend correlated well between those two methods, and the improved numerical method obtained more accurate results than those of the simplified theoretical method. Analytical and numerical results in normalized expressions systematically descripted the bending large-deformation behavior including position of neutral surface and critical buckling, wavelength, amplitude, shearing strain, macroscale compressive/tensile strain, buckled fiber strain, and actuation moment. To design a fiber-reinforced soft composite for use in engineering, the simplified theoretical method is used to predict trend and obtain approximate results for preliminary design, and the improved numerical method is further used to check and obtain more accurate results on detailed design stage.

Data-Driven Design Space Exploration and Exploitation for Design for Additive Manufacturing

Recently, design for additive manufacturing has been proposed to maximize product performance through the rational and integrated design of the product, its materials, and their manufacturing processes. Searching design solutions in such a multidimensional design space is a challenging task. Notably, no existing design support method is both rapid and tailored to the design process. In this study, we propose a holistic approach that applies data-driven methods in design search and optimization at successive stages of a design process. More specifically, a two-step surrogate model-based design method is proposed for the embodiment and detailed design stages. The Bayesian network classifier is used as the reasoning framework to explore the design space in the embodiment design stage, while the Gaussian process regression model is used as the evaluation function for an optimization method to exploit the design space in detailed design. These models are constructed based on one dataset that is created by the Latin hypercube sampling method and then refined by the Markov Chain Monte Carlo sampling method. This cost-effective data-driven approach is demonstrated in the design of a customized ankle brace that has a tunable mechanical performance by using a highly stretchable design concept with tailored stiffnesses.

Parametric study on the aeroelastic stability of rotor seals

Labyrinth seals are widely used in rotating machinery and can be prone to aeroelastic instabilities. The rapid development of computational fluid dynamics now provides a high-fidelity approach for predicting the aeroelastic behavior of labyrinth seals in three dimension and exhibits great potential within industrial application, especially during the detailed design stages. In the current publication a time-marching unsteady Reynolds-averaged Navier-Stokes solver was employed to study the various historically identified parameters that have essential influence on the stability of labyrinth seals. The findings from the numerical approach agree well with analytical criteria in determining the overall stability of the seal structure while being able to capture the acoustic behavior of the upstream or downstream large cavities and its influence on the inter-fin cavities. The high-fidelity approach provides additional insights on the effects of nodal diameter, travelling wave direction, pressure ratio, and the linearity of the phenomenon for relatively large vibration amplitudes, all of which can aid during the design space exploration.

A meta-model approach for formal specification and consistent management of multi-LOD building models

The design of a building is a collaborative process among experts from multiple disciplines. Using Building Information Modeling (BIM), a model is developed through multiple refinement stages to satisfy various design and engineering requirements. Such refinements of geometric and semantic information are described as levels of development (LOD). Thus far, there is no method to explicitly define an LOD’s requirements nor to precisely specify the uncertainties involved. Furthermore, despite the insufficient information in the early design stages, a BIM model appears precise and certain, which can lead to false assumptions and model evaluations, for example, in the case of energy efficiency calculations or structural analyses. Hence, this paper presents a multi-LOD meta-model to explicitly describe an LOD’s requirements, incorporating the potential fuzziness of both, geometric and semantic information of individual elements. The explicitly defined fuzziness can be taken into account when applying simulations or analyses for assessing the performance of different building design variants. To support the continuous elaboration of a building from the conceptual to the detailed design stages, the multi-LOD model makes it possible to ensure the consistency of the geometric and semantic information as well as the topological coherence across the different LODs. The feasibility of the approach is demonstrated by its prototypical implementation as a web-server and user-interface, providing a means for managing and checking the exchange requirements both at the meta-level and for concrete building model instances. The paper is concluded with a case study of a real-world construction project that demonstrates the use of the meta-model to support model analysis and the decision-making process.

THE METHOD OF IDENTIFYING THE PARAMETERS OF THE UNIVERSAL MODEL OF FAILURES APPROXIMATING THE GENERALIZED CURVE OF THE FAILURE RATE OF ELECTRONIC PRODUCTS

In the process of developing electronic systems at different stages of development, reliability indicators are evaluated with varying degrees of accuracy. Refined calculation of reliability at the stage of detailed design is carried out taking into account operating conditions, environmental factors and actual coefficients of the electrical load of radio elements. The “guidelines for calculating the reliability of devices and systems” currently in force in enterprises consider that all failures of radio elements are considered catastrophic (sudden). This does not take into account the processes of deterioration of elements and deterioration of parameters, that is, the process of gradual failure of radioelements. The resulting reliability estimates are pessimistic (the estimates of reliability indicators are significantly underestimated — evaluation errors range from 30% to 80%), which forces developers to introduce additional unnecessary redundancy into the structure of the designed system. The required number of spare parts for system operation also increases significantly. Therefore, the authors propose a new universal model of failures of products of electronic equipment (hereinafter referred to as radio elements), which takes into account sudden and gradual failures. The universal model is constructed using a composition of exponential and diffusive non-monotonic distribution of failures of radio elements. A method has been developed for determining the parameters of the universal failure model, which allows approximating the generalized curve of the intensity of failures of radio elements (the generalized failure curve of the “reliability bath”). This allows the use of reliability statistics, which are systematized in the “Reliability Guide for Electronic Products (Radio Elements)”. The authors have determined analytical expressions for the probability of trouble-free operation, the distribution function, the distribution density and the failure rate of the universal mathematical model of radio element failures. For practical application, three types of nomograms were developed. The proposed method for determining the parameters of the universal mathematical model of failures of radioelements allows developers: to develop mathematical models of the reliability of electronic systems in the design process, taking into account sudden and gradual failures of elements; to carry out calculations of indicators of reliability, durability of devices and the number of spare parts with high accuracy and reliability; remove excess redundancy in the design of electronic systems; reduce to 30-40 percent the volume of the required number of spare parts for the technical operation of systems.

Push button design requirements and relations to button architecture elements

The automotive industry supply chain has been subjected to new and global competition pressures, which are pushing for collaborative, interdependent and strategic product development partnerships among its agents, with the objective of improving the processes and responsiveness to product engineering requirements. Thus, some research has been dedicated to the analysis and translation of these user needs into product engineering requirements in order to provide methods to increase the conversion responsiveness. However, there is an additional conversion phase which is the definition of the product architecture to meet those requirements. So, the objective of this paper is to present a method and case study where button parameters are related to its architecture elements by applying Morphological Analysis and Artificial Neural Networks on the data collected from measurements made on in – car radio interfaces. The precision power of the models was demonstrated, meaning that it is possible to have an expected haptic behavior for the button, predicted in the form of a set of relevant haptic characteristics, based on the button architecture, and so, facilitating the initial detail design stages of in-car radio interfaces and potentially increasing its responsiveness to the client needs.

Integrating building information modeling and life cycle assessment in the early and detailed building design stages

In the early building design stage, there are numerous uncertainties due to the lack of information on materials and processes. Designers therefore cannot quantify the environmental impacts of buildings in order to evaluate the environmental performance of their designs early on. In this paper, life cycle assessment (LCA) and building information modeling (BIM) are carried out in the early and detailed building design stages. The method is applied to a residential building in Québec, Canada. The BIM is conducted with Revit, and the LCA with openLCA. To prepare the Revit outputs as the appropriate inputs of the LCA model, a functional database was developed. It includes all building assemblies, layers and possible materials commonly found in residential buildings in Québec. The ecoinvent database was used to source of life cycle inventory (LCI) data for each material. To manage information uncertainty in the early design stage, a probability function was assigned to each material. At the detailed design stage, all material types and quantities were specified in BIM file, which was used in the LCA study. The environmental impacts of the building stages and assemblies were calculated to determine the best building assembly options from an environmental perspective—a process that could guide building designers in the environmental assessments of their designs, making it possible to select more sustainable materials for each assembly and thus reduce the environmental impacts of the building.