Benny Raphael

Empirical Analysis of the Determinants of Organizational Flexibility in the Construction Business

Flexibility has been touted as an important requirement for firms to survive and prosper in turbulent and volatile economic environments. The aim of this research is to investigate the relevance of organizational flexibility management to construction firms, because firms that are more flexible are more likely to survive and prosper than less flexible firms. More specifically, the objectives are to define a model that will allow contractors to understand the complex factors that contribute to organizational flexibility; ascertain whether organizational flexibility should be treated as a uni- or multidimensional construct; and identify the key determinants that drive organizational flexibility. A two-pronged research method with exploratory interviews and an industrywide survey was adopted. Data were collected from face-to-face interviews with construction industry experts. The data collection instrument for the survey was a structured questionnaire specifically designed for this study. By using structural...

Optimal Sensor Placement for Time-Dependent Systems: Application to Wind Studies around Buildings

Warm climates pose challenges to building energy consumption and pedestrian comfort. Knowledge of the wind flow around buildings can help address these issues through improving natural ventilation, energy use, and outdoor thermal comfort. Computational fluid dynamics (CFD) simulations are widely used to predict wind flow around buildings, despite the large discrepancies that often occur between model predictions and actual measurements. Wind speed and direction exhibit a high degree of variability that adds uncertainties in modeling and measurements. Although some studies focus on methods to evaluate and minimize modeling uncertainties, sensor placement has been mostly based on subjective judgment and intuition; no systematic methodology is available to identify optimal sensor locations prior to field measurement. This work proposes a methodology for systematic sensor placement for situations when no measurement data are available and knowledge of the wind environment around buildings is limited. Sequential sensor placement algorithms and criteria are used to identify sensor configurations based on CFD simulation predictions at plausible locations. Optimal sensor configurations are compared for their ability to improve wind speed predictions at another location where no measurements are taken. The methodology is applied to two full-scale building systems of varying size. Results show that the methodology can be applied prior to field measurement to identify optimal configurations of a limited number of sensors that improve wind speed predictions at unmeasured locations

Tsunamis: Some pre‐emptive disaster planning and management issues for consideration by the construction industry

Purpose – Tsunamis are a rare but devastating form of natural disaster that has been documented since early civilization. Throughout history, many major tsunamis have impacted on the worlds coastlines, causing heavy loss of lives and damage to properties. While the Sumatran tsunami in December 2004 demonstrated the sheer scale of destruction, there remains little understanding of the implications such obliteration have for disaster planning and management in the construction industry. The purpose of this paper is to raise the awareness of these implications and address some of the pertinent issues. Design/methodology/approach – The threat from tsunamis for an island state like Singapore cannot be ignored. A general study of tsunami dynamics is carried out and applied to model the worst scenario if tsunamis were to hit Singapore. Unique problems relating to such a scenario are subsequently highlighted to extrapolate an understanding of how the construction industry should now react even before the disaster strikes. Findings – There appear to be some potential danger and immense uncertainties to the immediate coastline of Singapore in the event of a tsunami. Faced with these uncertainties, the local construction industry needs to recognise such challenges and develop appropriate policies and strategies way ahead to account for disaster planning and management. Practical implications – While tsunami warning systems have been put in place, tsunamis cannot be stopped. The construction industry has a significant role to play in minimising destruction through appropriate building codes, materials, designs, enforcement and preventive maintenance of infrastructure. Originality/value – The paper raises the issues of disaster planning and management caused by tsunamis and prompts the construction industry into taking appropriate and timely action to ward off what can be an extremely threatening event to both lives and properties.

Hierarchical Sensor Placement Using Joint Entropy and the Effect of Modeling Error

Good prediction of the behavior of wind around buildings improves designs for natural ventilation in warm climates. However wind modeling is complex, predictions are often inaccurate due to the large uncertainties in parameter values. The goal of this work is to enhance wind prediction around buildings using measurements through implementing a multiple-model system-identification approach. The success of system-identification approaches depends directly upon the location and number of sensors. Therefore, this research proposes a methodology for optimal sensor configuration based on hierarchical sensor placement involving calculations of prediction-value joint entropy. Computational Fluid Dynamics (CFD) models are generated to create a discrete population of possible wind-flow predictions, which are then used to identify optimal sensor locations. Optimal sensor configurations are revealed using the proposed methodology and considering the effect of systematic and spatially distributed modeling errors, as well as the common information between sensor locations. The methodology is applied to a full-scale case study and optimum configurations are evaluated for their ability to falsify models and improve predictions at locations where no measurements have been taken. It is concluded that a sensor placement strategy using joint entropy is able to lead to predictions of wind characteristics around buildings and capture short-term wind variability more effectively than sequential strategies, which maximize entropy.

A preference driven multi-criteria optimization tool for HVAC design and operation

Abstract This paper discusses the issue of selecting the design solution that best accords with an articulated preference of multiple criteria with an acceptable performance band. The application of a newly developed multi-criteria decision-making tool called RR-PARETO2 is presented. An example of HVAC design is used to illustrate how solutions could be selected within a multi-criteria optimization framework. In this example, five criteria have been selected, namely, power consumption, thermal comfort, risk of airborne infection of influenza and tuberculosis and effective differential temperature (Δt eq) of body parts. The goal is to select the optimal air exchange rate that makes reasonable trade-offs among all the objectives. Two scenarios have been studied. In the first scenario, there is an influenza outbreak and the important objective is to prevent the spread of infection. In the second scenario, energy prices are high and the primary objective is to reduce energy. In both scenarios, RR-PARETO2 algorithm selects solutions that make reasonable trade-offs among conflicting objectives. The example illustrates how objectives such as reduction of airborne disease transmission and maximizing thermal comfort can be incorporated in the design of a practical, full-scale HVAC system.

Active Control of Daylighting Features in Buildings

: Due to increasing awareness of the importance of energy efficiency, daylighting features such as light shelves are becoming more and more popular. A light shelf is a horizontal or inclined projection with a high reflectivity meant to increase the depth of daylight penetration into a room. Currently, a light shelf is treated as a passive design element. It is designed to maximize the average distribution of daylight during the operating hours of a building and its geometry is not adapted to the changing conditions during the day. This article discusses a methodology for the active control of light shelves. A light shelf system whose geometry can be adapted is presented. The control of this system is treated as a global optimization problem. Geometrical parameters of light shelves are computed in real time to minimize the energy required for artificial lighting. An example of an office building is taken to illustrate the hourly energy savings possible through active control. It is demonstrated that building automation and control have considerable potential for energy savings.

Computational fluid dynamics study and evaluation of different personalized exhaust devices

This article investigates the performance of three different types of personalized exhaust devices. A top-personalized exhaust, which is a round device just above the human head; a shoulder-personalized exhaust, which consists of two local exhaust devices installed at the chair just above shoulder level; and a chair-personalized exhaust, which is at the upper part of a chair just behind the human head, were simulated, evaluated, and compared numerically using the computational fluid dynamics method. Two seated occupants representing healthy and infected manikins equipped with two types of personalized ventilation devices in a simulated consulting room in a healthcare center were modeled. Two indices—personalized exposure effectiveness and inhaled fraction—were introduced to evaluate the improvement of general inhaled air quality after adding different types of personalized exhaust devices and to compare the performance of different kinds of personalized exhaust devices with respect to the healthy manikins exposure to exhaled contaminated air. The computational fluid dynamics models were validated with a set of experiments conducted in an environmental chamber. The results indicate that all the three personalized exhaust devices might be able to reduce the transmission of exhaled air between occupants. The lowest inhaled fraction was achieved by the combination of a vertical desk grill and a top-personalized exhaust. However, only the shoulder-personalized exhaust device has the potential to improve the amount of personalized ventilation air in the inhaled air.

Mathematical Models for Predicting Organizational Flexibility of Construction Firms in Singapore

The ability to predict and develop organizational flexibility is important for firms to survive and prosper in volatile business environments. The aim of this study is to investigate the constituents of and the constructs for predicting organizational flexibility. The specific objectives are to ascertain the relative importance of different constituents of flexibility and to construct and validate mathematical models to predict organizational flexibility of Singaporean construction firms. The research was conducted by a questionnaire survey and data were collected by face-to-face interviews with 41 construction industry experts. Three mathematical models were developed and validated by using the structural equation modeling (SEM) technique. The validation data consisted of ratings provided by four subject matter experts whose data were not used in the model development. The results show that the mathematical model for predicting strategic flexibility is able to predict to a good level of accuracy. The mod...

Performance evaluation of a novel personalized ventilation–personalized exhaust system for airborne infection control

In the context of airborne infection control, it is critical that the ventilation system is able to extract the contaminated exhaled air within the shortest possible time. To minimize the spread of contaminated air exhaled by occupants efficiently, a novel personalized ventilation (PV)-personalized exhaust (PE) system has been developed, which aims to exhaust the exhaled air as much as possible from around the infected person (IP). The PV-PE system was studied experimentally for a particular healthcare setting based on a typical consultation room geometry and four different medical consultation positions of an IP and a healthy person (HP). Experiments using two types of tracer gases were conducted to evaluate two types of PE: Top-PE and Shoulder-PE under two different background ventilation systems: Mixing Ventilation and Displacement Ventilation. Personalized exposure effectiveness, intake fraction (iF) and exposure reduction (ε) were used as indices to evaluate the PV-PE system. The results show that the combined PV-PE system for the HP achieves the lowest intake fraction; and the use of PE system for the IP alone shows much better performance than using PV system for the HP alone.

Feature selection using stochastic search: An application to system identification

System identification using multiple-model strategies may involve thousands of models with several parameters. However, only a few models are close to the correct model. A key task involves finding which parameters are important for explaining candidate models. The application of feature selection to system identification is studied in this paper. A new feature selection algorithm is proposed. It is based on the wrapper approach and combines two algorithms. The search is performed using stochastic sampling and the classification uses a support vector machine strategy. This approach is found to be better than genetic algorithm-based strategies for feature selection on several benchmark data sets. Applied to system identification, the algorithm supports subsequent decision making.