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The purpose of this paper is to investigate the development process of the fire whirl in the fixed-frame facility and focus on the impacts of the fire whirl’s vortex core on the formation and flame structure of the fire whirl.

The complex turbulent reacting flame surface is captured by the large eddy simulation turbulence closure coupled with two sub-grid scale (SGS) kinetic schemes (i.e. the chemistry equilibrium and steady diffusion flamelet). Numerical predictions are validated thoroughly against the measurements by Lei et al. (2015) with excellent agreements. A double maximum tangential velocity refinement approach is proposed to quantify the vortex cores’ instantaneous location and region, addressing the missing definition in other studies.

The numerical results show that the transition process of the fire whirl is dominated by the vortex core movement, which is related to the centripetal force. The unsteadiness of the fully developed fire whirl was found depending on the instantaneous fluctuation of heat release rate. The steady diffusion flamelet scheme is essential to capture the instantaneous fluctuation. Furthermore, the axial velocity inside the vortex core is the key to determining the state of fire whirl.

Due to intensive interactions between buoyant fires and ambient rotating flow, the on-set and formation of fire whirl still remain largely elusive. This paper focused on the transition process of fire whirl between different development stages. This paper provides insights into the transition process from the inclined flame to the fire whirls based on the centripetal force.

This paper presented and compared two SGS kinetic schemes to resolve the fire whirl development process and the unsteadiness of its vortical structures. The modelling framework addresses the shortcoming of previous numerical studies where RANS turbulence closure and simplified combustion kinetics was adopted. Numerical results also revealed the fire whirl transition process and its relationship to centripetal force.

The purpose of this study is to review and summarise the existing available literature on lightweight cladding systems to provide detailed information on fire behaviour (ignitibility, heat release rate and smoke toxicity) and various test method protocols. Additionally, the paper discusses the challenges and provides updated knowledge and recommendation on selective-fire mechanisms such as rapid-fire spread, air cavity and fire re-entry behaviours due to dripping and melting of lightweight composite claddings.

A comprehensive literature review on fire behaviour, fire hazard and testing methods of lightweight composite claddings has been conducted in this research. In summarising all possible fire hazards, particular attention is given to the potential impact of toxicity of lightweight cladding fires. In addition, various criteria for fire performance evaluation of lightweight composite claddings are also highlighted. These evaluations are generally categorised as small-, intermediate- and large-scale test methods.

The major challenges of lightweight claddings are rapid fire spread, smoke production and toxicity and inconsistency in fire testing.

The review highlights the current challenges in cladding fire, smoke toxicity, testing system and regulation to provide some research recommendations to address the identified challenges.

Modelling of the multiproject cash flow decisions in a contracting firm facilitates optimal resource utilization, financial planning, profit forecasting and enables the inclusion of cash‐flow liquidity in forecasting. However, a great challenge for contracting firm to manage his multiproject cash flow when large and multiple construction projects are involved (manipulate large amount of resources, e.g. labour, plant, material, cost, etc.). In such cases, the complexity of the problem, hence the constraints involved, renders most existing regular optimization techniques computationally intractable within reasonable time frames. This limit inhibits the ability of contracting firms to complete construction projects at maximum efficiency through efficient utilization of resources among projects. Recently, artificial neural networks have demonstrated its strength in solving many optimization problems efficiently. In this regard a novel recurrent‐neural‐network model that integrates multi‐objective linear programming and neural network (MOLPNN) techniques has been developed. The model was applied to a relatively large contracting company running 10 projects concurrently in Hong Kong. The case study verified the feasibility and applicability of the MOLPNN to the defined problem. A comparison undertaken of two optimal schedules (i.e. risk‐avoiding scheme A and risk‐seeking scheme B) of cash flow based on the decision maker's preference is described in this paper.

Optimizing both qualitative and quantitative factors is a key challenge in solving construction finance decisions. The semi‐structured nature of construction finance optimization problems precludes conventional optimization techniques. With a desire to improve the performance of the canonical genetic algorithm (CGA) which is characterized by static crossover and mutation probability, and to provide contractors with a profit‐risk trade‐off curve and cash flow prediction, an adaptive genetic algorithm (AGA) model is developed. Ten projects being undertaken by a major construction firm in Hong Kong were used as case studies to evaluate the performance of the genetic algorithm (GA). The results of case study reveal that the AGA outperformed the CGA both in terms of its quality of solutions and the computational time required for a certain level of accuracy. The results also indicate that there is a potential for using the GA for modelling financial decisions should both quantitative and qualitative factors be optimized simultaneously.

This paper presents a comparison of numerical predictions employing a Computational Fluid Dynamics fire model against a series of turbulent buoyant fire experiments recently carried out in a two‐room compartment structure by Nielsen and Fleischmann at the University of Canterbuty, New Zealand. The model incorporates turbulence, combustion, soot generation and radiation due to a fire. An evaluation of the various approaches—volumetric heat source approach or a more sophisticated handling the fire through a combustion model—is carried out. The effect of radiation due to combustion products and soot is also investigated. The model considering combustion with radiation contribution by both the combustion products and soot provides the best agreement between the predicted results and measured data. The presence of soot is seen to significantly augment the global radiation process within the two‐compartment enclosure.

This study delineates the effect of cover thickness on reinforced concrete (RC) columns and beams under an elevated fire scenario. Columns and beams are important load-carrying structural members of buildings. Under all circumstances, the columns and beams were set to be free from damage to avoid structural failure. Under the high-temperature scenario, the RC element may fail because of the material deterioration that occurs owing to the thermal effect. This study attempts to determine the optimum cover thickness for beams and columns under extreme loads and fire conditions.

Cover thicknesses of 30, 40, 45, 50, 60 and 70 mm for the columns and 10, 20, 25, 30, 35, 40, 50, 60 and 70 mm for the beams were adopted in this study. Both steady-state and transient-state conditions under thermomechanical analysis were performed using the finite element method to determine the heat transfer through the RC section and to determine the effect of thermal stresses.

The results show that the RC elements have a greater influence on the additional cover thickness at extreme temperatures and higher load ratios than at the service stages. The safe limits of the structural members were obtained under the combined effects of elevated temperatures and structural loads. The results also indicate that the compression members have a better thermal performance than the flexural members.

Numerical investigations concerning the high-temperature behavior of structural elements are useful. The lack of an experimental setup encourages researchers to perform numerical investigations. In this study, the finite element models were validated with existing finite element models and experimental results.

The obtained safe limit for the structural members could help to understand their resistance to fire in a real-time scenario. From the safe limit, a suitable design can be preferred while designing the structural members. This could probably save the structure from collapse.

There is a lack of both numerical and experimental research works. In numerical modeling, the research works found in the literature had difficulties in developing a numerical model that satisfactorily represents the structural members under fire, not being able to adequately understand their behavior at high temperatures. None of them considered the influence of the cover thickness under extreme fire and loading conditions. In this paper, this influence was evaluated and discussed.

The purpose of this study is to develop optimal evacuation plan to provide valuable theoretical and practical insight in the fire evacuation work of similar structures, by proposing a systematic simulation-based guided-evacuation agent-based model (GAM) and a three-stage mathematical evacuation model to investigate how to simulate, assess and improve the performance efficiency of the evacuation plan.

The authors first present the self-evacuation and guided-evacuation models to determine the optimal evacuation plan in ship chamber. Three key performance indicators are put forward to quantitatively assess the evacuation performance within the two fire scenarios. The evacuation model in tower is built to obtain the dividing points of the three different fire evacuation plans.

The study shows that the optimal evacuation plan determined by the GAM considering social relationships effectively relieves the congestion or collision of evacuees and improves the evacuation uniformity. The optimal evacuation plan not only solves the crush caused by congestion or collision of evacuees but also can greatly shorten the evacuation time for passenger ship fire.

This study establishes the GAM considering the interactive evacuee characteristics and the proportion of evacuees guided by the crew members to make the optimal evacuation plan more time-efficient. The self-evacuation process is simulated to assess the performance of the guided-evacuation strategies, which are used to verify the effectiveness and feasibility of the optimal evacuation plan in this research.

This study aims to numerically investigate the flow features and mixing/combustion efficiencies in a turbulent reacting jet in cross-flow by a hybrid Eulerian-Lagrangian methodology.

A high-order hybrid solver is employed where, the velocity field is obtained by solving the Eulerian filtered compressible transport equations while the species are simulated by using the filtered mass density function (FMDF) method.

The main features of a reacting JICF flame are reproduced by the large-eddy simulation (LES)/FMDF method. The computed mean and root-mean-square values of velocity and mean temperature field are in good agreement with experimental data. Reacting JICF’s with different momentum ratios are considered. The jet penetrates deeper for higher momentum ratios. Mixing and combustion efficiency are improved by increasing the momentum ratio.

The authors investigate the flow and combustion characteristics in subsonic reacting JICFs for which very limited studies are reported in the literature.

This study aims to apply association rule mining (ARM) to uncover specific associations between operating components of a chiller system and improve its coefficient of performance (COP), hence reducing the electricity use of buildings with central air conditioning.

First, 13 operating variables were identified, comprising measures of temperatures and flow rates of system components and their switching statuses. The variables were grouped into four bins before carrying out ARM. Strong rules were produced to associate the variables and switching statuses with different COP classes.

The strong rules explain existing constraints on practising chiller sequencing and prioritise variables for optimisation. Based on strong rules for the highest COP class, the optimal operating strategy involves rescheduling chillers and their associated components in pairs during a high load operation. Resetting the chilled water supply temperature is the next best strategy, followed by resetting the condenser water entering temperature, subject to operating constraints.

This study considers the even frequency method with four bins only. Replication work can be done with other discretisation methods and different numbers of classes to compare potential differences in the bin ranges of the optimised variables.

The strong rules identified by ARM highlight associations between variables and high or low COPs. This supports the selection of critical variables and the operating status of system components to maximise the COP. Tailor-made optimisation strategies and the associated electricity savings can be further evaluated.

Previous studies applied ARM for chiller fault detection but without considering system performance under the interaction of different components. The novelty of this study is its demonstration of ARM’s intelligence at discovering associations in past operating data. This enables the identification of tailor-made energy management opportunities, which are essential for all engineering systems. ARM is free from the prediction errors of typical regression and black-box models.

In this chapter we investigate the role of family-specific factors in facilitating or constraining business exit in family firms. Family business literature seems to have an implicit bias toward continuity and persistence in the founder's business. This is explained by heavy emotional involvement and development of path-dependent core competences over generations. However, several long-lived family firms were able to successfully exit the founder's business. Exit allowed them to free significant strategic resources, which were later reinvested in exploiting novel entrepreneurial opportunities. Our aim is to investigate the process of exit from the founder's business in family firms, to explain both triggers and obstacles to decommitment and de-escalation. We address this issue through the study of the Italian Falck Group's exit from the steel industry in the 1990s, followed by successful startup of a renewable energy business. By carefully triangulating different data sources and different voices within and outside the controlling family, we develop a framework describing family-specific facilitators and inhibitors of business exit, and subsequent startup of a new business. Three types of family-specific factors emerge as relevant in shaping a family firm's likelihood and speed of exit from a failing business: family-related psychological triggers and obstacles to business exit; family-specific components of the structural de-escalation context; family responses to ensuing de-escalation and exit needs. The emerging framework offers a more nuanced interpretation of decommitment activities in family firms, pointing to the differential role family-specific factors may play as facilitators or inhibitors of business exit. We also suggest how these family-specific results may contribute to a deeper understanding of exit in nonfamily firms. Our results also have practical implications for family business entrepreneurial management. Actively managing the different determinants of exit choices that emerged from our study will set the stage for de-escalation from a failing course of action – a dynamic capability all family firms should learn and practice if they intend to transfer their entrepreneurial orientation to next generations.