Cost estimation of structural skeleton using an interactive automation algorithm: A conceptual approach

This paper addresses a new concept for generating bills of quantities (B.o.Qs) using AutoCAD drawings for a building project, which demonstrates the application of Industry Foundation Class (IFC), developed by International Alliance for Interoperability (IAI). The procedure considers types of materials and the structural shapes of the AutoCAD drawings to compute the cost of the structural skeleton elements using interactive automation. The main concept focuses on using layer computation of the AutoCAD drawing after converting it into a drawing inter-exchangeable file format (DXF). Once the coordinates are detected, it is easier to determine the area and volume for any structural shape, including circles and polygons. The extracting method is a new technique for structural engineers and quantity surveyors to estimate required material for beam, columns, slabs and foundations. The algorithm extracts and recognizes the layers and objects from a two dimensional DXF drawing along with the coordinates information. The results obtained using this technique are more accurate and reliable than manual procedures or any other traditional techniques. In this paper, an automated and interactive procedure for B.o.Q computation is demonstrated. The process involves a user-friendly interface, dynamic linking to the structural drawings and tracking of B.o.Q modifications at the same time.     

Examining the role of amenities in migration decisions: A structural estimation approach

I develop a discrete choice dynamic migration model to examine the importance of amenity values in immigrants' migration decisions. The model accounts for differentials in both wages and location‐specific amenities as determinants of migration decisions, and the size of migrants' networks is allowed to influence the value of the US location choice as well. By estimating the model using panel data from the Mexican Migration Project, I find that Mexican migrants place substantial value on amenities in the United States, which are shown to fall precipitously with migrants' age. Simulation results from policy experiments indicate that Mexican immigrants are more responsive to a policy that reduces the amenity values related to unauthorized US residence than to an increase in the number of border patrol officers.     

On an implicit stress-calculation algorithm for a multidimensional constitutive law using a skeleton curve

In this paper, we present an implicit stress-calculation algorithm for a multidimensional constitutive law using a one-dimensional skeleton curve and a hysteresis curve. To consider the hysteretic behavior of soils, one-dimension skeleton curves (e.g., the Hardin–Drnevich model, Ramberg–Osgood (RO) model, and general hyperbolic equation (GHE) model) are widely used. In a multidimensional analysis, there are several methods for extending a constitutive law using a skeleton curve into multiple dimensions. However, because these methods are suitable for an explicit integration stress-calculation scheme, a calculated stress does not satisfy the function of skeleton curve when a large incremental strain is imposed in one step. In this paper, to resolve this problem, a nonlinear stress–strain relation using a skeleton curve and an implicit stress-calculation algorithm is presented. In addition, we show an example of an application of the GHE/RO model to the proposed algorithm.     

Cost optimization of a composite floor system using an improved harmony search algorithm

In this study, cost optimization of a composite floor system is performed utilizing the harmony search algorithm and an improved harmony search algorithm. These algorithms imitate the musical performance process that takes place when a musician searches for a better state of harmony, similar to the optimum design process which looks for the optimum solution. A composite floor system is designed by the LRFD-AISC method, using a unit consisting of a reinforced concrete slab and steel beams. The objective function is considered as the cost of the structure, which is minimized subjected to serviceability and strength requirements. Examples of composite floor systems are presented to illustrate the performance of the presented algorithms.     

A conceptual model of people's approach to sanitation

Sanitation is a term primarily used to characterize the safe and sound handling (and disposal) of human excreta - or simply, people's approach to take-care of their (unavoidable) primal urge. According to the recent Human Development Report 2006 Global access to proper sanitation stands at approximately 58% with 37% being a conservative estimate both for South Asia and Sub-Saharan Africa. Various multi-million dollar sanitation programmes the world over have had little success, often due to inadequate understanding of people's sanitation approach. Sanitation approach includes the perception, feel and practices involved in satisficing the primal need to defecate and urinate (and their disposal). This paper presents a structure to understand the nature of psycho-socio-economic influences that determine societal approach to sanitation. Societies across the globe have evolved imbibing diverse influences attributed to the local environment, religion, cultural practices, war, etc. While a civilization's living environment reflects these influences in their built-environment characteristics, the influences are often deep-rooted and can be traced to the way the community members satisfice their need to defecate and urinate (sanitation approach). The objective of this paper is to trace the various approaches that diverse societies/civilizations, over time, across the world have had towards sanitation, and present a structure to articulate and understand determining factors. Sanitation also involves other domestic (solid and liquid) waste disposal but in the context of this paper the scope of sanitation has been restricted to human excreta alone. The structure presented and discussed in this paper would be useful in understanding a community better in terms of providing appropriate sanitation. It is hoped that this structure be considered as a basis for further refinement and detailed research into each of the factors determining people's sanitation approach.     

差分传声器阵列期望最大化多声源方位估计方法

2016年8月6日定稿摘要针对小尺寸传声器阵列多声源方位估计易受混响噪声影响的问题,提出了一种适用于差分传声器阵列的期望最大化多声源方位估计方法。首先,该方法利用期望最大化算法求解出各个时频点瞬时方位估计所应满足的高斯混合模型参数;然后,通过时频点分离技术估计出各声源的方位值。针对现有的硬、软时频点分离技术应用于差分传声器阵列所存在的缺陷,还提出了一种改进的时频点分离方法,该方法融合了软、硬分离方法所具有的优点,有效降低了时频点分离结果对混响噪声的敏感性。仿真和实测实验结果表明:相较于现有的差分传声器阵列多声源估计方法,所提方法在混响噪声环境下具有更高的估计精度和稳健性能。     

Protocol analysis of designers using an interactive evolutionary computation

This paper explores the problem-solving behavior of people in design activities through a protocol analysis of verbal reports on the interior work design process simulated by an interactive evolutionary computation (IEC). The protocol analysis method was used to explore the ways of thinking of the participants throughout the process. The analysis reveals that different parts of the interior scene have different effects on the evaluations, and people tend to use the same evaluation criteria continuously on several images. This kind of behavior is consistent with that of professional designers in past studies and is revealed applicable to non-professionals in the current research.     

A socio-technical approach to post-occupancy evaluation: interactive adaptability in domestic retrofit

Understanding the process of domestic retrofit is important for learning and innovation. This is particularly the case for low carbon retrofits such as those undertaken under the UK's Retrofit for the Future (RftF) programme, with its aim to achieve an overall 80% carbon reduction by 2050. Current post-occupancy evaluation (POE) research has both theoretical and methodological limitations with implications for technical and behavioural research in the built environment. Drawing on relevant ideas and concepts from social practice theory and science and technology studies, principally prefiguration (constraints/enablement), black-boxing, heating and cooling practices, this paper demonstrates how the relationship between buildings and people could be reconceptualized as mutually constitutive and co-evolving through a process of ‘interactive adaptation’. The concept of ‘interactive adaptation’ is explored through a novel approach to integrating physical and social data collected from a sample of dwellings selected from the RftF programme. Analysis yields insights into the influences and pathways of interactive adaptation resulting from retrofit technology and practices. The implications of these insights for policy-makers, the research community and practitioners are discussed: end-use energy demand policy needs to be informed by a socio-technical approach.     

A conceptual framework to support solar PV simulation using an open-BIM data exchange standard

With the construction industry moving rapidly towards Building Information Modelling (BIM), it is essential that various analysis tools used in the Architecture, Engineering and Construction (AEC) domain are interoperable with a non-proprietary open BIM schema such as the Industry Foundation Classes (IFC). The UK government will be requiring fully-collaborative BIM in all public sector projects by 2016 and is also chasing the target of achieving zero-carbon buildings by 2019. This dual target will require the use of renewable energy analysis tools in the early stages of the building design process and establish the need for these tools to be IFC-compliant. This paper presents a conceptual framework for developing IFC-compliant renewable energy simulation tools using a multi-model concept in which the IFC data model provides partial input data required to run simulation models. A prototype has been developed as a ‘proof-of-concept’ for an IFC-compliant solar PV simulation tool. The prototype has been validated against other solar PV simulation tools such as PV*Sol, RETScreen® and HOMER to provide credibility to the simulation model. The developed conceptual framework is applicable not only to solar PV simulation but other renewable energy simulation models as well, thereby making an IFC-compliant renewable energy modelling tool capable of conducting, energy, carbon emissions and financial analysis.     

On the estimation of spatial stochastic frontier models: an alternative skew-normal approach

The Annals of Regional Science - This paper deals with an alternative approach to combine spatial dependence and stochastic frontier models using a large statistical literature on skew-normal...     

Cost premium prediction of certified green buildings: A neural network approach

Built environment has a substantial impact on the economy, society, and the environment. Along with the increasing environmental consideration of the building impacts, the environmental assessment of buildings has gained substantial importance in the construction industry. In this study, an artificial neural network model is built to predict cost premium of LEED certified green buildings based on LEED categories. To verify the viability of the model, multiple regression analysis is used as a benchmarking model. After validating the prediction power of the neural network model, a global sensitivity analysis is utilized to provide a better understanding of possible relationships between input and output variables of the prediction model. Sustainable Sites and Energy & Atmosphere LEED categories were found to have the highest sensitivity in cost premium prediction. In this study, our goal was to reveal the significant relationships between LEED categories and the cost premium, and offer a decision model that can guide owners to estimate cost premiums based on sought LEED credits.     

Modelling of structural response and optimization of structural control system using neural network and genetic algorithm

This paper proposes an integrated approach to the modelling and optimization of structural control systems in tall buildings. In this approach, an artificial neural network is applied to model the structural dynamic responses of tall buildings subjected to strong earthquakes, and a genetic algorithm is used to optimize the design problem of structural control systems, which constitutes a mixed‐discrete, nonlinear and multi‐modal optimization problem. The neural network model of the structural dynamic response analysis is included in the genetic algorithm and is used as a module of the structural analysis to estimate the dynamic responses of tall buildings. A numerical example is presented in which the general regression neural network is used to model the structural response analysis. The modelling method, procedure and the numerical results are discussed. Two Los Angeles earthquake records are adopted as earthquake excitations. Copyright © 2000 John Wiley & Sons, Ltd.     

Discretization of 2D random fields: A genetic algorithm approach

The random fields are widely used in the literature to include the random spatial variability of material properties, geometrical dimensions and loads into the mathematical models describing the behaviour of the engineering structures. In practice, a discretization procedure is necessary to reduce a continuous random field to a finite set of random variables. It is clear that the accuracy of the discretization is a key point for any subsequent probabilistic investigation of the structural performance. Indeed it is meaningful to formulate a discretization error estimator to quantify the accuracy of the discretization and to require that the approximated random field fulfils a prescribed target accuracy. The discretization of a random field can be formulated as an optimization problem, where the optimization variable is the finite number of random variables involved in the representation of the random field and the objective function depends on the discretization error estimator and on the target accuracy. The advantage of the formulation of the optimization problem depends on the availability of a simple, accurate and versatile numerical approach. A genetic algorithm is proposed in this paper to achieve an optimal discretization of two-dimensional (2D) homogeneous random fields represented by the Karhunen–Loeve series expansion. The numerical procedure is applied to the discretization of 2D random fields describing the random spatial fluctuations of the concrete properties in a bridge deck.     

A new approach for automation of location-based earthwork scheduling in road construction projects

Accurate information of working locations is vital for efficient resource planning, safety of the construction site and monitoring the weekly progress of earthworks, which is missing in the existing linear scheduling methods. Construction managers have to depend on the subjective decisions for resources allocation and progress monitoring from location aspects. This has caused uncertainties in planning and scheduling, and consequently delays and cost overruns of projects. In this context, a prototype computer-based model was developed using the theory of the location-based planning. An arithmetic algorithm was designed by incorporating road design data, sectional quantities, variable productivity rates and haulage distance. This paper focuses on the improvement and demonstration of the model functions through a case study experiment, which include the automatic generation of location-based earthwork schedules and the optimisation of the weekly resource allocation when and where necessary from the location aspects, considering different options such as construction sequences of the cut/fill sections, site access points and the equipment sets with known productivity rates. The study concluded that the model is a decision supporting tool that assists in the resources planning, identifying time–space congestion, monitoring the activities progress on a weekly basis from the location aspects, and reducing the gap when communicating the scheduling information amongst the construction site teams.     

Dynamic origin‐destination flow estimation using automatic vehicle identification data: A 3D convolutional neural network approach

Dynamic origin‐destination (OD) flow estimation is one of the most fundamental problems in traffic engineering. Despite numerous existing studies, the OD flow estimation problem remains challenging, as there is large dimensional difference between the unknown values to be estimated and the known traffic observations. To meet the needs of active traffic management and control, accurate time‐dependent OD flows are required to understand time‐of‐day traffic flow patterns. In this work, we propose a three‐dimensional (3D) convolution‐based deep neural network, “Res3D,” to learn the high‐dimensional correlations between local traffic patterns presented by automatic vehicle identification observations and OD flows. In this paper, a practical framework combining simulation‐based model training and few‐shot transfer learning is introduced to enhance the applicability of the proposed model, as continuously observing OD flows could be expensive. The proposed model is extensively tested based on a realistic road network, and the results show that for significant OD flows, the relative errors are stable around 5%, outperforming several other models, including prevalent neural networks as well as existing estimation models. Meanwhile, corrupted and out‐of‐distribution samples are generated as real‐world samples to validate Res3D's transferability, and the results indicated a 60% improvement with few‐shot transfer learning. Therefore, this proposed framework could help to bridge the gaps between traffic simulations and empirical cases.     

Modeling post-fire behavior of aluminum structural components using a maximum temperature approach

Aluminum alloys exhibit permanent degradation of material strength subsequent to reaching temperatures above 200 °C. While modeling of aluminum structural components during fire is becoming more heavily researched, modeling response of aluminum structures following fire events has still not been explored. Previous research suggests that the post-fire strength of AA6061 is heavily correlated to the maximum temperature reached during the fire. This research uses the maximum exposure temperature as an input to finite element simulations of a small scale aluminum beam to predict the post-fire behavior of the beam. Results of the simulations were compared to a set of post-fire thermo-mechanical experiments. Samples were heated using a radiative source, water quenched, and then loaded to failure in a four point bending configuration. The simulated thermal response of the aluminum was within 10% of measured values across the entire side of the beam. Prediction of the unexposed mechanical response was within 5% of experimentally measured response. The post-fire peak bending load from simulations generally over-predicted the experimentally measured value while predictions of the flexural stiffness were within 15% of experimental results.     

Optimum selection of photovoltaic modules using probabilistic approach based on capacity factor estimation

In this paper, the optimum selection of photovoltaic module using probabilistic techniques based on capacity factor estimation is proposed. The approach entails modelling the solar irradiance characteristics of the site by fitting probability distributions to the irradiance data for different hours of a typical day in each month of the year. The parameters of the probability distribution that best fits the solar irradiance data for a particular hour are thereafter used to estimate the capacity factor of different designs of PV modules. The module with the highest average capacity factor across all the months is identified as the best suited module for the given site. The proposed technique is investigated using 5 years data (2008–2012) of solar irradiance and temperature. The choice of the year of observation of the data was due to accuracy and completeness of the data for the period. The data sheets of 10 commercially available PV modules were also obtained from different manufacturers. The proposed method is simple, easy to use, and can be applied to any solar regimes around the world.     

Residential-commercial energy input estimation based on genetic algorithm (GA) approaches: an application of Turkey

The main objective of the present study is to develop the energy input estimation equations for the residential-commercial sector (RCS) in order to estimate the future projections based on genetic algorithm (GA) notion and to examine the effect of the design parameters on the energy input of the sector. For this purpose, the Turkish RCS is given as an example. The GA Energy Input Estimation Model (GAEIEM) is used to estimate Turkey’s future residential-commercial energy input demand based on GDP, population, import, export, house production, cement production and basic house appliances consumption figures. It may be concluded that the three various forms of models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies.     

Analysis of structural interaction in tunnels using the covergence–confinement approach

The rock-support interaction in tunnels is studied through the use of the convergence–confinement method. The equations that characterize the behaviour of the most important support types are given together with a set of conceptual interaction schemes. As far as the behaviour of the support is concerned, reference is made to the ultimate limit state concept, which is widely used in civil engineering. This approach is linked to the classical convergence–confinement method. The interaction between the temporary support system and the final lining is dealt with, and the noteworthy case of presupport ahead of the face, followed by a further internal support (usually steel sets and shotcrete) is also included. Finally, the ‘ground reaction curve of the reinforced tunnel’, which allows one to analyse the interaction between the reinforcement around the tunnel and supports, is introduced.