Fire fatality study

Over a six-year period, 530 fire fatalities resulting from 398 fires were studied in the State of Maryland. The study had two major objectives: (1) to determine the specific cause of death by a detailed autopsy stud of fire victims, and (2) to determine the specific cause of fatality-producing fire by an on-the-scene fire investigation. The fire fatality study was limited to residential fires and to fatalities that occurred within 6 h of the fire. The results of the toxicological analysis show that (1) 60% of the victims had a carboxyhemoglobin value greater than or equal to 50% carbon monoxide saturation, (2) an additional 20% had elevated carboxyhemoglobin with preexisting cardiovascular disease, (3) 11% of the victims had severe burns, (4) 9% were unexplained and (5) 40% of the victims had positive blood alcohol levels with 30% of these meeting the legal definition of intoxication (blood alcohol ≥0.1%). The fire investigations confirmed that the predominant fatal scenario is the cigarette ignition of upholstered furniture or bedding. This scenario accounted for 47% of the fires and 44% of the victims. Alcohol also appears to be significant factor in this scenario.     

Diode-pumped Nd:YAG laser with 38 W average power and user-selectable, flat-in-time subnanosecond pulses

A diode-pumped injection-seeded Nd:YAG laser system with an average output power of 38 W is described. The laser operates at 300 Hz with pulse energies up to 130 mJ. The temporal pulse shape is nominally flat in time and the pulse width is user selectable from 350 to 600 ps. In addition, the spatial profile of the beam is near top hat with contrast <10%.     

Measuring Productivity and Validating Microcomputer Simulation

Abstract: Computer simulation can provide an eficient and cost-effective method of analyzing project alternatives, resource constraints and potential progress. It is frequently performed to study the behavior of a system in an attempt to improve performance. There are many different analytical methods that can be used to plan or analyze a construction operation. However, in most cases, analytical techniques require abstractions which tend to reduce confidence in model predictions. These methods do, however, offer a basis for validating simulation results. This paper illustrates how Micro CYCLONE, a microcomputer-based simulation language, can be used to measure job productivity in construction. It also illustrates how BetaFit, a microcomputer-based program, can be used to model accurately and eficiently random processes for use in the simulation experiments. The paper also presents a framework for validating construction simulation by reviewing the application of two analytical methods. A roof truss process is modeled using the CYCLONE methodology and then validated using queueing theory and method productivity delay modeling to illustrate the various procedures.     

Quantitative Assessment for Piles Productivity Factors

The management process of any construction operation usually can be defined as a chain of decisions. A decision-maker can bid, plan, and organize the bored pile projects based on an accurate estimate of productivity. To estimate productivity efficiently, piling process qualitative and quantitative factors have to be considered. This paper focuses on assessing the effect of subjective factors on bored pile construction productivity. A productivity index (PI) model is developed to represent this subjective effect in refining productivity assessment using simulation and deterministic techniques. The analytic hierarchy process and fuzzy logic are used to develop the proposed PI model that relies on the actual performance of 10 main piling process subjective factors. Subjective data were collected from bored pile (drilled shaft) contractors considering these subjective factors. The developed PI model implementation to piling process resulted in PI=0.7. This value has been validated using simulation model outputs.     

Dynamic Programming Approach to Optimization of Site Remediation

Environmental restoration is a matter of national concern. Decades of abuse by industry, agriculture, and the military have caused devastating contamination of the earth, air, and water. The Department of Energy alone will spend hundreds of billions of dollars on containment and restoration. It is imperative that restoration costs are minimized. Every dollar spent on restoration is a dollar that will not go toward research, a dollar that will not go to upgrade our nation’s infrastructure. The work presented here uses cost as a decision variable in restoration projects. Contaminated sites frequently vary from one point to another in type and level of contamination. In addition, a single piece of property may contain several distinct contaminated areas, each of which has characteristics unlike any of the other areas. Thus one should look at optimizing the selection of remediation technologies to address the variation. A methodology has been developed that will optimize the selection of remediation technologies based on cost. This methodology uses geostatistics and dynamic programming to break a site into discrete cells and then select the optimal sequence of remediation technologies.     

Designing industrial systems with a weak utility supply

A number of issues related to successful power system design practices for maximum harmony between industrial energy users, their utility suppliers and the local community are discussed in this article. In many cases, industrial power system engineers concentrate on “the plant side of the meter” and utility engineers concentrate on “the utility side of the meter“. The authors show, however, that it is important for the industrial power engineer to be aware of the utility perspective and vice verse. If not, design flaws may not appear until production begins. Problems occurring at startup that were not anticipated will require significant investments, not necessarily monetary, by all parties involved     

Pile Construction Productivity Assessment

Bored piles are vital elements for highway bridge foundation. A large number of factors oversees productivity and cost estimation processes for piles, which creates many problems for the time and cost estimators of such process. Therefore, current study is designed to diagnose these problems and assess productivity, cycle time, and cost for pile construction using the artificial neural network (ANN). Data were collected for this study through designated questionnaires, site interviews, and telephone calls to experts in different construction companies. Many variables have been considered to manage the piling construction process. Three-layer, feed forward, and fully connected ANNs were trained with an architecture of seven input neurons, five output neurons, and different hidden layer neurons. The ANN models were validated and proved their robustness in output assessments. Three sets of charts have been developed to assess productivity, cycle time, and cost. This research is relevant to both industry practitioners and researchers. It provides sets of charts for practitioners’ usage to schedule and price out pile construction projects. In addition, it provides researchers with a methodology of applying ANN to pile construction process, its limitation, and future suggestions.     

Efficient Flow Computation on Massive Grid Terrain Datasets

As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at finer resolutions. Processing the massive datasets involved in such applications presents significant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. In this paper we present efficient algorithms for flow routing on massive grid terrain datasets, extending our previous work on flow accumulation. Our algorithms are developed in the framework of external memory algorithms and use I/O-techniques to achieve efficiency. We have implemented the algorithms in the Terraflow system, which is the first comprehensive terrain flow software system designed and optimized for massive data. We compare the performance of Terraflow with that of state-of-the-art commercial and open-source GIS systems. On large terrains, Terraflow outperforms existing systems by a factor of 2 to 1,000, and is capable of solving problems no system was previously able to solve.