Minimum Construction Cost Research Articles

Numerical modeling of transport roads in open pit mines

Transport of overburden and mineral raw materials in surface mining is one of the most complex and costly processes today. Good transport roads are essential for successful transportation by trucks in open pit mines. Poor design, and maintenance of the roads has the greatest impact on the high transport costs and possible risks in terms of security. Numerical modeling was performed to analyze the effects of the properties of the built-in materials used in the construction of roads, the thickness of the layers and the interaction of tires with the road surface. The distribution of stress and strain determined in the construction of a road depends on the characteristics of the road and the structure and mass of the truck. For this reason, numerical modeling and computer simulation is considered a very suitable method in the design of roads, because in a short period of time and at a lower cost calculations for the construction of a large number of models can be implemented and the best model available will be chosen. The most favorable construction will be considered to be the one that will, at minimum construction costs and with low costs of maintenance, enable the efficient use of transport equipment for a longer period of exploitation.

A mathematical optimisation model for the design and detailing of reinforced concrete beams

An evolutionary metaheuristic optimization model for sizing reinforced concrete beams is presented. The proposed optimization model transcends ones in the literature as it is able to consider characteristic concrete strength (fck), cross-section area and reinforcement bars' diameters as discrete design variables, thus representing a more realistic model. The goal is to minimize construction costs via configuring cross-sectional dimensions, determining reinforcement layouts, and defining fck. The design constraints formulated in the mathematical model proposed are related to structural integrity, considering ultimate limit state, serviceability limit state, and good construction practices. A finite element method program was developed to obtain the stresses and strains of beams, geometries, and load forces. Additionally, a longitudinal reinforcement database generator was developed, ensuring that the reinforcement layouts generated are within codes of practice. A Genetic Algorithm was adopted to solve the resulting optimisation problem. Results of case studies demonstrate that the cost variance implications are directly related to the reinforcement detailing arrangements, with 3.63% to 17.07% improvements in costs that are achieved when compared with other studies in the literature.

Multi-objective optimization of stepped spillway and stilling basin dimensions

Abstract In the present paper, an optimization procedure is proposed for stepped spillway design dimensions, which leads to maximum energy dissipation rate and minimum construction cost, considering independently the chute cost and stilling basin cost. Three independent objective functions are thus simultaneously satisfied. The procedure involves four main tools: the multi-objective particle swarm optimization method (MOPSO) to find Pareto solutions in one run, the K-means clustering algorithm to reduce the size of the obtained non-dominated solutions, the pseudo-weight vector approach (PWV) to facilitate the decision making and to select some adequate solutions, and finally, CFD simulations to analyze the retained optimal solutions. The suitability of the proposed procedure is tested through an example of application. As results, a set of 20 solutions with different satisfaction levels is found and compared to existing solutions. A multi-objective optimization problem may have many different solutions; the originality of the present work lies in the proposed procedure, which explores several possible solutions and reduces their number to give help to the decision making. Furthermore, an approximate expression of spillway total cost is also derived as a function of flow energy dissipation rate.

Settlement-based cost optimization of geogrid-reinforced pile-supported foundation

Cost optimization of Geogrid-Reinforced Pile-Supported Foundation (GRPSF) requires the minimum construction cost among all design alternatives within both ultimate limit state (ULS) and serviceability limit state (SLS) criteria. Usually, the optimization is conducted by selecting a limited number of design alternatives based on experience and then comparing them, which often does not lead to the real optimal design. This paper presents a novel optimization framework to systematically determine the design parameters to achieve the minimum construction cost for GRPSF, considering both ULS and SLS constraints that are relevant to post-construction performance and constructability. This framework is a hybrid of surrogate modeling and Finite Element Method (FEM) to calculate the post-construction settlement of GRPSF and search for the optimal design. Genetic Algorithm improved Black Hole Algorithm (BH-GA) was developed to determine the optimal values of design variables, including pile length and spacing, pile cap geometry, and geogrid layers and layout. The proposed approach can quickly identify the optimal design by exhausting all possible combinations of design parameters. Two well-documented case histories of GRPSF were redesigned using this framework, which validated its applicability and effectiveness in optimizing the design of GRPSF.

Towards design of compound channels with minimum overall cost through grey wolf optimization algorithm

Abstract The significant role of open channels in agriculture include supplying drinking water, industry, irrigation and flood control, making these hydraulic structures an integral part of the water conveyance system. Determination of optimum dimensions with minimum construction costs is considered as the primary concern when designing artificial open channels. To achieve this, the compound channels were evaluated with the following constraints, viz. composite roughness, velocity, Froude number and channel stability. Grey wolf optimization (GWO) was used to determine the optimal geometry of the channel. Optimization results clearly showed that the variation of roughness coefficient and the increase of factor of safety increased costs by 60 and 20% respectively. The optimum suitable cross-section for the compound channels was obtained by conducting various model scenarios.

OPTIMIZATION OF SPLINE PARAMETERS WHEN DESIGNING ROUTES OF LINEAR STRUCTURES

It considers the problem of approximating a discrete sequence of points on a plane by a spline consisting of line segments conjugated by circular arcs with unknown boundaries and the number of spline elements. This article is a continuation of the article published in N 6, 2019. This problem arises when designing the longitudinal profile of new and reconstructed railways and highways. The fundamental differences of the considered problem from the problems solved in the theory of splines and its applications are shown. A two-stage scheme is proposed: at the first stage, using a special dynamic programming algorithm, the number of elements of the spline and the approximate values of its parameters that satisfy all the constraints are determined. At the second stage, this result is used as an initial approximation to optimize the spline parameters using a special nonlinear algorithm. Significant simplifications of the algorithm of the first stage are implemented in comparison with the previously published one, due to the absence of clothoids when conjugating straight lines and curves. The necessity of the second stage in the design of new roads is substantiated to take into account the interconnection of spline elements in embankments and in excavations, if embankments will be constructed from excavation soil, and optimization is performed according to the criterion of minimum construction costs. A new nonlinear programming algorithm is proposed based on the construction of a basis in zero spaces of matrices of active constraints and the correction of this basis in an iterative process when changing the set of active constraints. It is shown how to find the direction of descent and solve the problem of excluding constraints from the active set without solving systems of linear equations in general or by solving linear systems of low dimension. Instead of the traditionally used sum of squares of deviations of the approximated points from the spline, other models are proposed as a model of the objective function, taking into account the specifics of a specific design problem.

Route alignment planning for a new highway between two cities using Geoinformatics techniques

An attempt has been made to delineate and identify the alignment of a new route between two important cities of north India, Haridwar & Roorkee using Geoinformatics techniques. Geo-engineering parameters like slope, aspect, geology, land use, drainage and soil along with some techno-economical parameters have been used for this purpose. Multi-criteria weight method has been applied. Five weighting methods (AHP - Analytical Hierarchy Process, Rank Sum, Rank Reciprocal, Rank Exponent and Ratio Estimation) were applied simultaneously to eliminate biasness in weight assignment to the input parameters. The results show that AHP method is the best and ratio estimation method is the second best method for identification of optimum route alignment. Few more parameters were used for final selection of optimum route viz., minimum construction cost; minimum number of bridges and culverts on that route; maximum number of settlement within 5 km buffers on both sides of route; maximum number of tourist locations like temples, waterfalls, springs etc. within 5 km buffer zone on both side of route. The proposed route between Roorkee and Haridwar towns is only 29.22 km long (includes a 17.10 km long part of the existing road), the new road required is 12.12 km, while the existing longer route between Roorkee and Haridwar is 33 km (instead of 29.22 km). By using multi-criteria weighted methods of route alignment, a length of approximately 3.78 km can be avoided. It was also observed that slope, land use and drainage parameters are more sensitive for route alignment.

Optimum Hydraulic Design of Inverted Syphon Structure in Sewer System with a Case Study of Al-Hashmea Sewer Project

An inverted syphon is a hydraulic structure utilized to convey open channel flow under obstructions. This study focuses on identifying the safest and optimum design of a sewage inverted syphon to avoid intersection problems with immovable infrastructures. Hydraulic design requirements, inlet and outlet distribution rooms features and protection of expected loads on syphons’ pipes were taken under consideration in formulation the optimization model. Further, different pipes’ material, many levels of the design variables and parameters were incorporated in the model to highlight the effect of each variable on the optimum design. The objective function was the minimum construction cost, and the design requirements were presented as constraints in the model. Results demonstrated that the optimum design for discharges ranging from 0.38 m3/sec to 0.95 m3/sec was Poly Vinyl Chloride (PVC) syphon, but for other discharges the reinforced concrete type was the optimum. Compared to traditional design, the optimum solutions provide a significant cost reduction. Concrete inverted syphon was the optimum possible solution to solve intersection problem of Al-Hashmea sewer project to pass sewage flow under the railway.

The joint construction of goals and means as a solution for the problem of variability in behavior

The understanding of variability in behavior is extraordinarily difficult because behavior consists of actions that are purposeful processes directed to reach future results and psychological functions can deliberately be adjusted for this. The conventional method used in handling this problem is to make behavior in experiments as similar as possible to processes studied in the natural sciences. It is suggested this allows the revealing of simple mechanisms of behavior that are independent of purpose and deliberation. A sufficient basis of the simple mechanisms should elucidate purposefulness mechanistically. It is implicitly assumed this method defines the simple mechanisms unequivocally. The replication crisis hints this assumption is incorrect. Arocha (2021) suggests purpose is the essential component in understanding behavior. However, Arocha assumes no mechanistic explanations for goal-directed processes, thus restricting the usefulness of his ideas. I suggest the goal and means of an action are constructed jointly through the criterion of minimal construction costs. This mechanistically determines actions.

A deep reinforcement learning approach to mountain railway alignment optimization

AbstractThe design and planning of railway alignments is the dominant task in railway construction. However, it is difficult to achieve self‐learning and learning from human experience with manual as well as automated design methods. Also, many existing approaches require predefined numbers of horizontal points of intersection or vertical points of intersection as input. To address these issues, this study employs deep reinforcement learning (DRL) to optimize mountainous railway alignments with the goal of minimizing construction costs. First, in the DRL model, the state of the railway alignment optimization environment is determined, and the action and reward function of the optimization agent are defined along with the corresponding alignment constraints. Second, we integrate a recent DRL algorithm called the deep deterministic policy gradient with optional human experience to obtain the final optimized railway alignment, and the influence of human experience is demonstrated through a sensitivity analysis. Finally, this methodology is applied to a real‐world case study in a mountainous region, and the results verify that the DRL approach used here can automatically explore and optimize the railway alignment, decreasing the construction cost by 17.65% and 7.98%, compared with the manual alignment and with the results of a method based on the distance transform, respectively, while satisfying various alignment constraints.

Are low-income mass housing envelops energy efficient and comfortable? A multi-objective evaluation in warm-humid climate

This study evaluates and compares the performance of the commonly constructed mass housing envelops in India with alternative building envelop constructions. These alternative construction scenarios are created with a material library comprising of the available alternative roofing and walling system combinations including some common emerging construction technologies standardized and advocated by the Building Materials and Technology Promotion Council of India. The common trend of housing envelop constructions in the country involves ordinary burnt brick walls and reinforced cement concrete roofing and beam-column system which is referred to as the base case building envelop in our study. We consider initial investment costs, thermal comfort perception and the initial embodied energy in a multi-objective evaluation framework for assessing free running building envelops. Rat trap bonded brick walls, glass fibre reinforced gypsum construction, light gauge framed steel (LGFS) constructions, monolithic concrete (MC) construction system, reinforced concrete ribbed roof and compressed stabilized earth block (CSEB) walls and CSEB filler roof slabs make repeated appearances in the multi-objective optimal solution sets or Pareto optimal solution sets. CSEB construction has lowest initial embodied energy, LGFS gives minimal thermal discomfort whereas MC construction system reports least construction cost. A predominance of lean envelop constructions is observed in the Pareto optimal solution sets considering minimization of construction cost, thermal discomfort and construction embodied energy.

Optimized allocation of scooter battery swapping station under demand uncertainty

Appropriately allocating battery swapping stations (BSSs) encourages drivers to use battery-operated scooters (ES) for reducing air pollution. The stochastic nature of battery swapping (BS) has not been widely discussed. Also, relatively few models have been proposed to, with particular reference to the possible demand for battery swapping, optimize the BSS locations and the appropriate number of batteries provided for the users of ESs to swap depleted batteries. Hence, this study aims to develop an optimized allocation model of grid-based scooter BSS (OAMSBSS) to be used to solve the abovementioned problem.First, using Monte Carlo simulation for problem-solving operations, along with the consideration given to the traffic flow and population distribution, the stochastic BS model used to predict the demand of stochastic BS was proposed to estimate the various possible scenarios of BSD. Each scenario involved the location decisions and the time distribution for battery swapping demand. Optimizers were adopted to optimally allocate the BSS to both satisfy the BS demand scenarios and achieve the minimal BSS construction cost. The optimized locations of BSSs are considered to not only cost lower land rentals but also help a large number of drivers faced with the problem of the demand for BS services.

APPLICATIONS OF OPTIMIZATION TECHNIQUES IN CONSTRUCTION MANAGEMENT

The time management for a construction project can better justify by using optimization methods. Nowadays many computerized software are used to explore, to design, to analyze, and to solve different engineering problems. Construction management is not only a concept to manage a project work under the guidelines of 5M aspects, while it is actually a whole of initialization and termination of the particular construction project work. This concept can better understand by incorporating optimization techniques to find feasible solutions of different situations arise during the execution of an activity. An activity may be a matter of complication if it is started without planning. The worse results of activity reflected at end of the work in the form of uneconomical achievement. Thus, to overcome these unforeseen situations, it may be suitable to solve them using optimization methods and get an optimal result. KEYWORDS – Optimization Techniques, Construction Project Management, Linear Programming Problem, Minimum Construction Cost.

Seismic risk management through insurance and its sensitivity to uncertainty in the hazard model

Acknowledging the devastating consequences of past earthquakes, current research efforts focus on the development of tools for assessing and controlling the risk and losses associated with future earthquakes, in addition to trying to minimize construction costs. Apart from providing a control of these levels, earthquake engineering can also provide solutions to manage the financial implications of the expected hazardous events. The first part of this article focuses on the management of the expected losses through the mechanism of transfer of the financial risk via earthquake insurance. Various insurance models are explained and applied in different case studies, and numerous analyses are performed across Europe, for a benchmark four-storey reinforced-concrete frame building. The results highlight significant variation in the premiums with seismicity, design practices and properties of the insurance model. It is crucial that any mitigation or transfer framework should use probabilistic methods to consider the uncertainties inherent in the hazard and structural response estimates. For example, different studies for the same region often indicate considerable differences in seismic hazard estimates. The uncertainty inherent in the hazard input model is transferred to and affects the results of the structural design and the performance assessment. Thus, the second part of the article investigates the impact of the epistemic uncertainty in the hazard model on the structural design and consequently the estimated future losses and risk levels, again for the benchmark building. First, a comparison is performed between the hazard data from two studies for different locations in Italy, in order to assess the possible range of variation in estimated hazard levels amongst different studies. The effects of these hazard variations on the seismic design and risk and loss metrics for the benchmark building are also investigated for these locations. Finally, a simplified approach for modelling hazard uncertainty is introduced and various sensitivity analyses are performed to investigate the effects of the hazard uncertainty across Europe. It is shown that hazard uncertainty can be of differing importance for the various involved stakeholders.

Numerical modeling of transport roads in open pit mines

Transport of overburden and mineral raw materials in surface mining is one of the most complex and costly processes today. Good transport roads are essential for successful transportation by trucks in open pit mines. Poor design, and maintenance of the roads has the greatest impact on the high transport costs and possible risks in terms of security. Numerical modeling was performed to analyze the effects of the properties of the built-in materials used in the construction of roads, the thickness of the layers and the interaction of tires with the road surface. The distribution of stress and strain determined in the construction of a road depends on the characteristics of the road and the structure and mass of the truck. For this reason, numerical modeling and computer simulation is considered a very suitable method in the design of roads, because in a short period of time and at a lower cost calculations for the construction of a large number of models can be implemented and the best model available will be chosen. The most favorable construction will be considered to be the one that will, at minimum construction costs and with low costs of maintenance, enable the efficient use of transport equipment for a longer period of exploitation.

Optimization of grade-separated road and railway crossings based on a distance transform algorithm

The design of grade-separated road and railway crossings can be complicated and time-consuming since the intersection point as well as the road and rail alignments should jointly optimize an objective such as minimum construction costs. Moreover, the design of grade-separated road and railway crossings should consider additional crossing constraints and possible revisions of the road alignments. However, research on alignment optimization with variable ends is scarce. In this article, a grade-separated road and railway crossing model is developed, the crossing point of which as well as both connection points with the road, are variable. Subsequently, by searching synchronously for the paths that connect different endpoints, a distance transform algorithm is applied. The effectiveness of the method is verified through a real-world case study. The results show that the proposed method can find various promising solutions that both satisfy multiple constraints and are considerable improvements on the designs produced by experienced human designers.

Optimal economic operation of liquid petroleum products pipeline systems

AbstractThe majority of overland transport needs for crude petroleum and refined petroleum products are met using pipelines. Numerous studies have developed optimization methods for design of these systems in order to minimize construction costs while meeting capacity requirements. Here, we formulate problems to optimize the operations of existing single liquid commodity pipeline systems subject to physical flow and pump engineering constraints. The objectives are to maximize the economic value created for users of the system and to minimize operating costs. We present a general computational method for this class of continuous, non‐convex nonlinear programs, and examine the use of pump operating settings and flow allocations as decision variables. The approach is applied to compute optimal operating regimes and perform engineering economic sensitivity analyses for a case study of a crude oil pipeline developed using publicly available data.

How public values theory can influence energy infrastructure planning: Exploring values articulation, time horizons, and substitutability through the Atlantic Coast pipeline

The transformation of energy infrastructure in the United States, specifically the expansion of the transportation network of natural gas pipelines, is garnering more public attention than ever before. Once built, energy infrastructure is long-lasting and exerts a strong influence on economic conditions, environmental integrity, and social behavior. Yet, clear, strategic energy plans are lacking and federal permitting focuses on economic factors. This research explores how public values theory can be operationalized to include noneconomic factors into planning for the transformation of energy infrastructure. However, there is a paucity of mechanisms to incorporate noneconomic values into decision-making processes related to energy infrastructure. Work remains to bridge theory and practice such that public values can shape planning and permitting processes. This research presents a case study on the Atlantic Coast Pipeline project, drawing upon survey data from 268 people and three workshops with 15 participants to inform the ongoing national debate on energy infrastructure. The survey analysis suggests three key determinants for pipeline infrastructure as illustrated by: i) models of scale (size and the proportional risk); ii) eminent domain (taking lands); and iii) protectionism (“Not In My BackYard,” or NIMBY). This research also showcases three alternative approaches on how to foster deliberative democratic processes with community members. This research extends the theoretical construct of public values theory by articulating mechanisms of action and assessing the efficacy of those mechanisms. Strategic planning for energy transitions and finding ways to reduce conflict may, in the long-term, minimize construction costs and address local concerns.

Integrating underground line design with existing public transportation systems to increase transit network connectivity: Case study in Greater Cairo

Connectivity is a significant problem in large-scale transit networks because the number of transfers required to conduct a trip is considered a discomfort by transit users. This paper presents a practical solution for an underground metro line planning problem by integrating existing bus and metro networks into a single connected transit network. The proposed method aims to obviate the usual combinatorial complexity when solving a transit route design problem. It aims to increase the overall transit system connectivity by selecting a consistent and non-demand-oriented criterion for the design. The metro lines are designed by minimizing passenger transfers through the transit network according to predefined demand node pairs. The design scheme offers a set of ring route alternatives for a sizeable case study in Greater Cairo. The case study selected sixteen traffic analysis zones, an existing metro network consisting of three main lines (113.6 km long), and twelve main bus lines (487.7 km long) for analysis. TransCAD software was used as the basis for coordinating the stations and lines of both the bus and metro systems. Subsequently, a passenger transfer counting algorithm was implemented to determine the number of transfers required between stations from each origin to each destination. A passenger origin–destination transfer matrix was created using the NetBeans integrated development environment to help determine the number of transfers required to complete trips on the transit network before and after proposing the new line. Based on the evaluation, the ring lines were highly efficient at significantly decreasing passenger transfers between stations with the minimum construction cost. This study will be of value during the strategic stages of the transit line design and will assist in rapidly generating initial solutions when certain demand information is unavailable.

Dynamic and consequential LCA aspects in multi-objective optimisation for NZEB design

Multi-objective optimisation coupled with building energy simulation (BES) and life cycle assessment (LCA) models is a promising method to eco-design net-zero energy buildings (NZEBs) in line with sustainable objectives such as UN SDG’s goals 7, 11, 12 and 13. This paper presents a method of building multi-objective optimisation based on NSGA-II coupled with the BES model COMFIE and the building LCA tool EQUER to identify NZEB designs that minimise construction costs and GHG emissions. A dynamic electricity mix model was implemented in LCA to evaluate more precisely time-related impacts of heating and solar photovoltaic production. Three different LCA approaches defining the multi-objective optimisation problem were compared: static LCA (considering an average annual electricity mix), dynamic attributionnal LCA (average hourly mix) and dynamic consequential LCA (marginal hourly mix). Results show minor differences in optimums quality between static and dynamic attributionnal approaches but important differences in optimums design parameters between attributionnal and consequential approaches. The influence of the LCA approach on multi-objective optimisation results emphasises the need to specify guidelines for practitioners about the choice of the LCA approach.