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Integrated project delivery (IPD) project that does not use multiparty agreement is identified as IPD-ish. The use of IPD-ish arrangement by incorporating integration practices in conventional contract can be viewed as the part of the adoption process of IPD. Moreover, inappropriate integration practices invite new forms of risks and the absence of multiparty agreement adds to the challenges of risk management in IPD-ish projects. This study discusses such challenges and proposes the use of joint risk management to address the potential pitfalls in IPD-ish arrangement.

A mixed research method was applied. First, the criticality of IPD-ish general and integration-specific risks was examined through a survey. Second, a real IPD-ish project was used to exemplify the use of joint risk management (JRM) to manage IPD-ish risks.

Two types of risks, namely integration risks (IRs) and general risks (GRs), are identified in IPD-ish projects. Two major findings for the IRs: (1) the most critical IRs are related to unbalanced incentivization and inefficient multidisciplinary teams; and (2) only team formation related pre-contract JRM strategies affect IRs. As for the GRs, the most critical ones are associated with design issues and can be effectively mitigated by post-contract JRM.

Using IPD-ish arrangement is an inevitable part of implementation of full IPD. This happens as many change-averse owners would like to test the integration principles using a conventional contract that they are familiar with. In fact, success in IPD-ish would pave the path for further adoption of IPD. This study offers insight into categorization of risks in IPD-ish projects. Appropriate use of post-contract and organization related pre-contract JRM would improve the chance of teasing out the values of IPD through IPD-ish arrangements. Care should be taken to introduce some contracting integration initiatives, such as risk/reward sharing incentive.

The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.

The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.

An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.

The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.

This research aims to create a methodology that integrates optimization techniques into preliminary cost estimates and predicts the impacts of design alternatives of steel pedestrian bridges (SPBs). The cost estimation process uses two main parameters, but the main goal is to create a cost estimation model.

This study explores a flexible model design that uses computing capabilities for decision-making. Using cost optimization techniques, the model can select an optimal pedestrian bridge system based on multiple criteria that may change independently. This research focuses on four types of SPB systems prevalent in Egypt and worldwide. The study also suggests developing a computerized cost and weight optimization model that enables decision-makers to select the optimal system for SPBs in keeping up with the criteria established for that system.

In this paper, the authors developed an optimization model for cost estimates of SPBs. The model considers two main parameters: weight and cost. The main contribution of this study based on a parametric study is to propose an approach that enables structural engineers and designers to select the optimum system for SPBs.

The implications of this research from a practical perspective are that the study outlines a feasible approach to develop a computerized model that utilizes the capabilities of computing for quick cost optimization that enables decision-makers to select the optimal system for four common SPBs based on multiple criteria that may change independently and in concert with cost optimization during the preliminary design stage.

The model can choose an optimal system for SPBs based on multiple criteria that may change independently and in concert with cost optimization. The resulting optimization model can forecast the optimum cost of the SPBs for different structural spans and road spans based on local unit costs of materials cost of steel structures, fabrication, erection and painting works.

The authors developed a computerized model that uses spreadsheet software's capabilities for cost optimization, enabling decision-makers to select the optimal system for SPBs meeting the criteria established for such a system. Based on structural characteristics and material unit costs, this study shows that using the optimization model for estimating the total direct cost of SPB systems, the project cost can be accurately predicted based on the conceptual design status, and positive prediction outcomes are achieved.

This study aims to investigate a new circuitous minichannel cold plate (MCP) design involving flow fragmentation. The overall thermal performance and the temperature uniformity analysis are performed and compared with the traditional serpentine design. The substrate thickness and its thermal conductivity are varied to analyse the effect of axial-back conduction due to the conjugate nature of heat transfer.

The traditional serpentine minichannel is modified into five new fragmented designs with two inlets and two outlets. A three-dimensional numerical model involving the effect of conjugate heat transfer with a single-phase laminar fluid flow subjected to constant heat flux is solved using a finite volume-based computational fluid dynamics solver.

The minimum and maximum temperature differences are observed for the two branch fragmented flow designs. The two-branch and middle channel fragmented design shows better temperature uniformity over other designs while the three-branch fragmented designs exhibited better hydrodynamic performance.

MCPs could be used as an indirect liquid cooling method for battery thermal management of pouch and prismatic cells. Coupling the modified cold plates with a battery module and investigating the effect of different battery parameters and environmental effects in a transient state are the prospects for further research.

The study involves several aspects of evaluation for a conclusive decision on optimum channel design by analysing the performance plot between the temperature uniformity index, average base temperature and overall thermal performance. The new fragmented channels are designed in a way to facilitate the fluid towards the outlet in the minimum possible path thereby reducing the pressure drop, also maximizing the heat transfer and temperature uniformity from the substrate due to two inlets and a reversed-flow pattern. Simplified minichannel designs are proposed in this study for practical deployment and ease of manufacturability.

Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the amount of deteriorate at any time, this paper aims to present a prognostics approach based on integrating optimize health indicator (OHI) and machine learning algorithm.

Proposed optimum prediction model would be used to evaluate the remaining useful life (RUL) of REBs. Initially, signal raw data are preprocessing through mother wavelet transform; after that, the primary fault features are extracted. Further, these features process to elevate the clarity of features using the random forest algorithm. Based on variable importance of features, the best representation of fault features is selected. Optimize the selected feature by adjusting weight vector using optimization techniques such as genetic algorithm (GA), sequential quadratic optimization (SQO) and multiobjective optimization (MOO). New OHIs are determined and apply to train the network. Finally, optimum predictive models are developed by integrating OHI and artificial neural network (ANN), K-mean clustering (KMC) (i.e. OHI–GA–ANN, OHI–SQO–ANN, OHI–MOO–ANN, OHI–GA–KMC, OHI–SQO–KMC and OHI–MOO–KMC).

Optimum prediction models performance are recorded and compared with the actual value. Finally, based on error term values best optimum prediction model is proposed for evaluation of RUL of REBs.

Proposed OHI–GA–KMC model is compared in terms of error values with previously published work. RUL predicted by OHI–GA–KMC model is smaller, giving the advantage of this method.

Due to the enormous increase in economic development, structural steel material gives an advantage for the construction of stadiums, factories, bridges and cities building design. The purpose of this study is to investigate the behaviour of bending, buckling and torsion for I-beam steel section with and without web opening using non-linear finite element analysis.

The control model was simulated via LUSAS software with the four main parameters which included opening size, layout, shape and orientation. The analysis used a constant beam span which is 3.5 m while the edge distance from the centre of the opening to the edge of the beam is kept constant at 250 mm at each end.

The analysis results show that the optimum opening size obtained is 0.65 D while optimum layout of opening is Layout 1 with nine web openings. Under bending behaviour, steel section with octagon shapes of web opening shows the highest yield load, yield moment and thus highest structural efficiency as compared to other shapes of openings. Besides, square shape of web opening has the highest structural efficiency under buckling behaviour. The lower buckling load and buckling moment contribute to the higher structural efficiency.

Further, the square web opening with counter clockwise has the highest structural efficiency under torsion behaviour.

This study aims to determine the effect of different friction stir welding (FSW) parameters on mechanical and metallurgical characteristics of aviation-grade AA8090 alloy joints.

Response surface methodology with central composite design is used to design experiments. The mechanical and microstructure characteristics of the weld joints have been studied through a standardized method, and the influence of threaded pins on the joint microstructure has also been assessed.

From a desirability strategy, the optimum parameters setting of the friction stir welding was the tool rotational speed (TRS) of 800, 1,100 and 1,400 rpm; tool traverse speed (TTS) of 20, 30 and 40 mm/min; and tilt angle 1°, 2° and 3° with different tool pin profiles, i.e. cylindrical threaded (CT), square threaded and triangular threaded (TT), for achieving the maximum tensile strength, yield strength (YTS) and % elongation as an output parameter. The TRS speed was the highest weld joint characteristics influencing parameter. Peak tensile strength (378 MPa), percentage elongation (10.1) and YTS (308 MPa) were observed for the optimized parametric value of TRS-1,400, TTS-40 mm/min and TA (3°) along with CT pin profile. Microstructure study of the welded surface was achieved by using scanning electron microscope of output parameters. When the tool rotation speed, tool transverse speed, tilt angle and tool profile are set to moderately optimal levels, a mixed mode of ductile and brittle fracture has been seen during the microstructure analysis of the welded joint. This has been aided by the material’s plastic deformation and the small cracks surrounding the weld zone.

From the reported literature, it has been observed that limited work has been reported on aviation-grade AA8090 alloys. Further thermal behavior of welded joints has also been observed in this experimental work.

This study aims to investigate and compare the characteristics of three topologies of moving-magnet linear oscillating actuator (LOA) based on their mover position. Positive aspects and consequences of every topology are demonstrated. Three topologies of axially magnetized moving-magnet LOA; outer mover, inner mover (IM) and dual stator (DS) are designed and examined. Due to its characteristically high thrust density and more mechanical strength, axially magnetized tubular permanent magnets (PMs) are used in these topologies.

LOAs are designed and optimized using parametric sweep, in term of design parameters and output parameters like thrust force, stroke and operating resonance frequency of the LOA. All the pros and cons of each topology are investigated and compared. Output parameters of the LOAs are compared using same size of the investigated LOAs. Mover mass, which plays a vital role in resonant operation, is analyzed for IM and DS designs. Investigated LOAs are compared with conventional designs of LOA for compressor in refrigeration system with regards of motor constant, stroke and thrust per PM mass.

This paper analyzes three topologies of moving-magnet LOAs. The basic difference between investigated LOAs is the radius of tubular-shaped mover from its central axis. All the design parameters are compared and concluded that thrust per PM mass of IMLOA is maximum. OMLOA provides maximum motor constant of value 180 N/A. DSLOA provides thrust force with motor constant 120 N/A and required intermediate materials of PMs. All the three designs give the best results in terms of motor constant and thrust per PM mass, compared to conventional designs of LOA.

This paper determines the impact of mover position from its central axis in a tubular-shaped moving-magnet LOA. This work is carried out in correspondence of latest papers of LOA.

This paper aims to present an improvement to the power quality of the grid by using a colliding body optimization (CBO) based proportional-integral (PI) compensated design for a grid-connected solar photovoltaic-fed brushless DC motor (BLDC)-driven water pumping system with a bidirectional power flow control. The system with bidirectional power flow allows driving the pump at full proportions uninterruptedly irrespective of the weather conditions and feeding a grid when water pumping is not required.

Here, power quality issue is taken care of by the optimal generation of the duty cycle of the voltage source converter. The duty cycle is optimally generated by optimal selection of the gains of the current controller (i.e. PI), with the CBO technique resulting in a nearly unity power factor as well as lower total harmonic distortion (THD) of input current. In the CBO technique, the gains of the PI controller are considered as agents and collide with each other to obtain the best value. The system is simulated using MATLAB/Simulink and validated in real time with OPAL RT simulator, OP5700.

It was found that the power quality of grid using the CBO technique has improved much better than the particle swarm optimization and Zeigler–Nichols approach. The bidirectional flow of control of VSC allowed for optimum resource utilization and full capacity of water pumping whatever may be weather conditions.

Improved power quality of grid by optimally generation of the duty cycle for the proposed system. A unit vector tamplate generation technique is used for bidirectional power transfer.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.