A Review of Pathways for Building Fire Spread in the Wildland Urban Interface Part II: Response of Components and Systems and Mitigation Strategies in the United States

Structure loss in wildland fires has significantly increased over the past few decades, affected by increased development in rural areas, changing fuel management policies, and climate change, all of which are projected to increase in the future. This paper is Part II of a two-part review, which presents a summary of fundamental and applied research on pathways to fire spread in the wildland urban interface. Part I discussed the fundamentals of wildland fire spread via radiative heat transfer, direct flame contact, and firebrand exposure. Here in Part II, we cover the response of building components and systems, as well as mitigation strategies used to prevent fire spread into and within communities in the United States. Post-fire investigations, full-scale structural testing, individual component testing, and combined systems or assembly testing have been used to identify building component and system vulnerabilities such as roofs, vents, siding, decks, fences, and mulch. Using results from these tests and investigations at different scales, some knowledge has been gained on specific vulnerabilities and the effectiveness of mitigation strategies, but a quantitative framework has not yet been established. On a community level, the layout of structures and the space between them has been shown to be incredibly important in mitigating wildfire risk. More locally, defensible space around homes has been effective in mitigating exposure from both radiation and direct flame contact. Firebrands still remain a challenge; however, many design recommendations have been proposed to harden structures against firebrand exposures. Recommendations for future research and development are also presented.     

Parametric estimation of change-points for actual event data in recurrent events models

Time to event data have long been important in many applied fields. Many models and analysis methods have been developed for this type of data in which each sample unit experiences at most a single end-of-life event.In contrast, many applications involve repeated events, where a subject or sampling unit experiences more than one event. There is growing interest in the analysis of recurrent events data, also called repeated events and recurrence data. This type of data arises in many fields. For example, the repair history of manufactured items can be modeled as recurrent events. In medical studies, the times of recurrent disease episodes in patients can also be modeled as recurrent events. In this paper we focus on medical applications (e.g. seizures, heart attacks, cancerous tumors, etc.). However, our proposed methodologies can be applied to other areas as well.For analyzing recurrence data, the first and perhaps most important step is to model the expected number of events, and sometimes this can be facilitated by modeling the cumulative intensity function or its derivative, the intensity rate function. One particular recurrent events scenario involves patients experiencing events according to a common intensity rate, and then a treatment may be applied. Assuming the treatment to be effective, the patients would be expected to follow a different intensity rate after receiving the treatment. Further, the treatment might be effective for a limited amount of time, so that a third rate would govern arrivals of the recurrent events after the effects of the treatment wore out. In this paper we model the intensity rate for such scenarios. In particular we allow models for the intensity rate, post-treatment, to be piecewise constant. Two estimators of the location of this change are proposed. Properties of the estimators are discussed. An example is studied for illustrative purposes.     

Crack propagation in brittle heterogeneous solids: Material disorder and crack dynamics

Crack propagation in a linear elastic material with weakly inhomogeneous failure properties is analyzed. An equation of motion for the crack is derived in the limit of slow velocity. Predictions of this equation on both the average crack growth velocity and its fluctuations are compared with recent experimental results performed on brittle heterogeneous materials (Ponson in Phys Rev Lett, 103, 055501; Måløy et al. in Phys Rev Lett, 96, 045501). They are found to reproduce quantitatively the main features of crack propagation in disordered systems. This theoretical framework provides new tools to predict life time and fracture energy of materials from their properties at the micro-scale.     

Characteristic time,developers’ behavior and leapfrogging dynamics of high-rise buildings

This paper suggests a plausible explanation for the spatial evolution of high-rise buildings. Contrary to intuitive expectations the histograms and spatial distribution in cities indicate peculiar and non-continuous patterns. These patterns evolve as a result of developers’ behavior in real-estate markets. One of the critical variables in decision-making of developers is time. Despite obvious differences in land prices within a particular real-estate market, differences in costs and prices are relatively small in comparison to differences in their time incidence. The paper presents a simple search model of land developer that suggests interesting explanation of the spatial sprawl of cities. The central parameter in our model is “characteristic time”, the period of time from the acquisition of initial property rights in the land and until the first return on the investment is realized. The model leads to leapfrogging patterns, particularly during downturn periods and explains the appearance of high-rise buildings in the urban periphery.     

Effect of composition of (La0.8Sr0.2MnO3-Y2O3-stabilized ZrO2) cathodes: Correlating three-dimensional microstructure and polarization resistance

Composite La_0.8Sr_0.2MnO₃ (LSM)-Y₂O₃-stabilized ZrO₂ (YSZ) cathodes with compositions ranging from 30:70 to 70:30 wt.% LSM:YSZ were studied both electrochemically and microstructurally. Polarization resistance was lowest for the 50 wt.% YSZ composition, and increased symmetrically as the composition deviated from this value. Serial-sectioning using focused ion beam-scanning electron microscopy was implemented to reconstruct the three-dimensional cathode microstructure. Various averaged structural parameters were determined versus composition, including phase volume fractions, surface area densities, total triple-phase boundary (TPB) densities, interfacial curvatures, phase tortuosities, and the levels of phase connectivity. Typically >90% of the pore and YSZ networks were found to be intra-connected to the surrounding phase, but the LSM networks showed lower connected fractions, as low as 37.5% for a LSM weight fraction of 30%. The composition dependences of the total TPB density and electrochemically-active TPB density (i.e., TPB's on three fully intra-connected phases) were shown to agree reasonably well with simple “sphere-packing” structural models. An electrochemical model that accounted for the linear-specific resistance of TPB's, phase intra-connectivity, and oxygen ion transport in the YSZ as influenced by its tortuosity, was found to provide reasonable agreement with the measured polarization resistance versus composition.     

Classification of signals by means of Genetic Programming

This paper describes a new technique for signal classification by means of Genetic Programming (GP). The novelty of this technique is that no prior knowledge of the signals is needed to extract the features. Instead of it, GP is able to extract the most relevant features needed for classification. This technique has been applied for the solution of a well-known problem: the classification of EEG signals in epileptic and healthy patients. In this problem, signals obtained from EEG recordings must be correctly classified into their corresponding class. The aim is to show that the technique described here, with the automatic extraction of features, can return better results than the classical techniques based on manual extraction of features. For this purpose, a final comparison between the results obtained with this technique and other results found in the literature with the same database can be found. This comparison shows how this technique can improve the ones found.