Finite element analysis with explicit time integration is widely used in commercial crash solvers to accurately simulate transient structural problems involving large-deformation and nonlinearity. Technological advances in computer software and hardware have expanded the boundaries of computational expense, allowing designers to analyse increasingly complex structures on desktop computers. This dissertation is a review of the use of finite element analysis for crash simulation, the principles of crashworthy design and a practical application of these methods and principles in the development of a concept energy absorber for a sailplane. Explicit nonlinear finite element analysis was used to do crash simulations of the glass, carbon and aramid fibre cockpit during the development of concept absorbers. The SOL700 solution sequence in MSC Nastran, which invokes the LS-Dyna solver for structural solution, was used. Single finite elements with Hughes-Liu shell formulation were loaded to failure in pure tension and compression and validated against material properties. Further, a simple composite crash box in a mass drop experiment was simulated and compared to experimental results. FEA was used for various crash simulations of the JS1 sailplane cockpit to determine its crashworthiness. Then, variants of a concept energy absorber with cellular aluminium sandwich construction were simulated. Two more variants constructed only of fibre-laminate materials were modelled for comparison. Energy absorption and specific energy absorption were analysed over the first 515 mm of crushing. Simulation results indicate that the existing JS1 cockpit is able to absorb energy through progressive crushing of the frontal structure without collapse of the main cockpit volume. Simulated energy absorption over the first 515 mm was improved from 2232 J for the existing structure, to 9 363 J by the addition of an energy absorber. Specific energy absorption during the simulation was increased from 1063 J/kg to 2035 J/kg. / MIng (Mechanical Engineering), North-West University, Potchefstroom Campus, 2015

Master of Science / Department of Civil Engineering / Sunanda Dissanayake / Rapid increases are estimated in the percentage of elderly among the U.S. population starting in 2010. A majority of the older Americans depend on automobiles to meet their transportation needs either because of lack of public transportation or by choice. Ninety percent of total trips made by the elderly are by personal vehicle and seventy percent of this number involves the elderly driving the vehicles. However due to the aging process, older drivers experience a natural decline in sensory, cognitive, and other mental and physical capabilities as compared to younger drivers. This situation, combined with an imperfect highway infrastructure is making older drivers one of the most critical groups in terms of highway safety, thus demanding safer driving conditions. Safety concern for older drivers arises when the fatality rate per mile driven is considered, as exposure is one of the crucial factors contributing to increased fatality risk of older drivers. Hence, exposure reported in Billion Vehicle Miles Traveled (BVMT) was considered for this study. Crash data and exposure data were used to compute the fatality rates. Sources for this data are the Fatality Analysis Reporting System (FARS) and National Household Travel Survey (NHTS). A basic characteristics study was completed to compare the fatality risk of younger (16-24 yrs), middle-aged (25-64 yrs), and older drivers (65+ yrs). Crash details were screened to study the characteristics of older drivers involved in fatal crashes. Risk for older drivers due to other involved drivers of all ages divided into groups was studied to understand their distribution. A number of statistical methods like the chi-square test of independence, odds ratio and double paired comparison estimates were applied to study contributing factors of older driver’s increased fatal crash involvement. Results from the characteristics study for the elderly indicate that a majority of fatal crashes occur under daylight conditions with relatively higher seatbelt usage and non-alcoholic driving on straight level roads, which are generally considered as safer driving conditions. Other factors studied include vehicle-related variables like body type; manner of collision; roadway-related variables like roadway function class, month of the crash, and day of the week; and driver-related variables like race. Roadway functional class, vehicle body type, travel speed, number of drunk drivers, and the month in which the fatality occurred were found to have strong correlation with age of the older driver. Results from paired comparisons were used to estimate the fatality risk of older occupants as drivers and passengers under two different conditions considered simultaneously. Older drivers were found to have more fatality risk compared to older passengers. Recommended measures are also discussed to enhance older driver safety in the U.S.

Tragically, traffic accidents involving drivers, motorcyclists and pedestrians result in thousands of fatalities worldwide each year. For this reason, making improvements to road safety and saving people's lives is an international priority. In recent years, this aim has been supported by Intelligent Transport Systems, offering safety systems and providing an intelligent driving environment. The development of wireless communications and mobile ad hoc networks has led to improvements in intelligent transportation systems heightening these systems' safety. Vehicular ad hoc Networks comprise an important technology; included within intelligent transportation systems, they use dedicated short-range communications to assist vehicles to communicate with one another, or with those roadside units in range. This form of communication can reduce road accidents and provide a safer driving environment. A major challenge has been to design an ideal system to filter relevant contextual information from the surrounding environment, taking into consideration the contributory factors necessary to predict the likelihood of a crash with different levels of severity. Designing an accurate and effective pre-crash system to avoid front and back crashes or mitigate their severity is the most important goal of intelligent transportation systems, as it can save people's lives. Furthermore, in order to improve crash prediction, context-aware systems can be used to collect and analyse contextual information regarding contributory factors. The crash likelihood in this study is considered to operate within an uncertain context, and is defined according to the dynamic interaction between the driver, the vehicle and the environment, meaning it is affected by contributory factors and develops over time. As a crash likelihood is considered to be an uncertain context and develops over time, any usable technology must overcome this uncertainty in order to accurately predict crashes. This thesis presents a context-aware pre-crash collision prediction system, which captures information from the surrounding environment, the driver and other vehicles on the road. It utilises a Dynamic Bayesian Network as a reasoning model to predict crash likelihood and severity level, whether any crash will be fatal, serious, or slight. This is achieved by combining the above mentioned information and performing probabilistic reasoning over time. The thesis introduces novel context aware on-board unit architecture for crash prediction. The architecture is divided into three phases: the physical, the thinking and the application phase; these which represent the three main subsystems of a context-aware system: sensing, reasoning and acting. In the thinking phase, a novel Dynamic Bayesian Network framework is introduced to predict crash likelihood. The framework is able to perform probabilistic reasoning to predict uncertainty, in order to accurately predict a crash. It divides crash severity levels according to the UK department for transport, into fatal, serious and slight. GeNIe version 2.0 software was used to implement and verify the Dynamic Bayesian Network model. This model has been verified using both syntactical and real data provided by the UK department for transport in order to demonstrate the prediction accuracy of the proposed model and to demonstrate the importance of including a large amount of contextual information in the prediction process. The evaluation of the proposed system delivered high-fidelity results, when predicting crashes and their severity. This was judged by inputting different sensor readings and performing several experiments. The findings of this study has helped to predict the probability of a crash at different severity levels, accounting for factors that may be involved in causing a crash, thereby representing a valuable step towards creating a safer traffic network.

published_or_final_version / abstract / Civil Engineering / Doctoral / Doctor of Philosophy

This thesis comprehends a series of nonlinear numerical studies with the finite element software's LS-Dyna and Impetus AFEA. The main focus lies on a comparative crash analysis of an aluminium beam profile which the company Sapa technology has used during their crash analysis. The aluminium profile has the characteristic of having different thickness over span ratios within the profile. This characteristic provided the opportunity to conduct a performance investigation of shell and solid elements with finite element analysis. Numerical comparisons were made between shell and solid elements where measurable parameters such as internal energy, simulation times, buckling patterns and material failures were compared to physical tests conducted prior to this thesis by Sapa technology. The performance investigation of shell and solid elements was initiated by creating models of the aluminium profile for general visualization and to facilitate the meshing of surfaces. The meshing procedure was considered to be an important factor of the analysis. The mesh quality and element orientations were carefully monitored in order to achieve acceptable results when the models were compared to physical tests. Preliminary simulations were further conducted in order to obtain a clear understanding of software parameters when performing crash simulations in LS-Dyna and Impetus AFEA. The investigated parameters were element formulations and material models. A general parameter understanding facilitated in the selection of parameters for actual simulations, where material failure and damage models were used. In conclusion, LS-Dyna was observed to provide a bigger internal energy absorption during the crushing of the beam with longer simulation times for solid elements when compared to shell elements. Impetus AFEA did on the other hand provide results close to physical test data with acceptable simulation times when compared to physical tests. The result difference obtained from the FE-software's in relation to physical crash experiments were considered to be varied but did indicate that shell elements were efficient enough for the specific profile during simulations with LS-Dyna. Impetus AFEA proved that the same time to be numerically efficient for energy approximations with solid elements refined with the third polynomial.

In this study, we capture the moderating effect of aggressive driving behavior while assessing the influence of a comprehensive set of variables on injury severity. In doing so, we are able to account for the indirect effects of variables on injury severity through their influence on aggressive driving behavior, as well as the direct effect of variables on injury severity. The methodology used in this study to accommodate the moderating effect of aggressive driving behavior takes the form of two models – one for aggressive driving and another for injury severity. These are appropriately linked to obtain the indirect and direct effects of variables. The data for estimation is obtained from the National Motor Vehicle Crash Causation Study (NMVCCS). From an empirical standpoint, we consider a fine age categorization until 20 years of age when examining age effects on aggressive driving behavior and injury severity. There are several important results from the empirical analysis. Young drivers (especially novice drivers between 16-17 years of age), drivers who are not wearing seat belt, under the influence of alcohol, not having a valid license, and driving a pickup are found to be most likely to behave aggressively. Situational, vehicle, and roadway factors such as young drivers traveling with young passengers, young drivers driving an SUV or a pick-up truck, driving during the morning rush hour, and driving on roads with high speed limits are also found to trigger aggressive driving behavior. In terms of vehicle occupants, the safest situation from a driver injury standpoint is when there are 2 or more passengers in the vehicle, at least one of whom is above the age of 20 years. These and many other results are discussed, along with implications of the result for graduated driving licensing (GDL) programs. / text

The overall aim was to elucidate the effects of vehicle passengers on young drivers. This generated two specific aims and four papers. The first aim was to investigate the crash risk for young drivers with passengers and to establish whether such accidents involve any special circumstances compared to those that occur without passengers. This goal was achieved by analysing accident and exposure data from two registers. The second objective was to analyse the group processes that develop between four young men in a vehicle and to ascertain how those interactions affect driving behaviour. Those issues were addressed by performing an observational study of twelve young men driving an instrumented vehicle in real traffic with and without passengers. The interactions between the vehicle occupants were video and audio recorded, and the driving behaviour was registered in various ways. The results show that drivers with passengers have a lower crash risk compared to those driving alone regardless of the driver’s age, although this effect is weaker for young drivers (especially males) than for other age groups. Compared to driving alone, driving with passengers for young drivers is more extensively associated with single-vehicle crashes that occur at night, on weekends, and in rural areas on roads with higher speed limits, and it leads to more severe outcomes. It has also been found that the passengers sometimes try to induce the young drivers to act in either safer or more dangerous ways, although the drivers very often resist urging and coaxing from their passengers. Cohesion is another factor that affect the driver-passenger group: a high level of cohesion, especially task cohesion, is associated with a low number of unsafe driving actions. Consequently, it seems that the presence of passengers is not enough to ensure safe driving—substantial group cohesion is also necessary for such behaviour. / Det övergripande syftet med denna avhandling var att studera passagerares effekt på unga förare, vilket genererade två delsyften och fyra delarbeten. Det första delsyftet var att undersöka olycksrisken för unga förare med passagerare och att ta reda på om dessa olyckor skedde under några speciella omständigheter. För att få svar på syftet gjordes en registerstudie där olycks- och exponeringsdata från två olika register analyserades. Det andra delsyftet var att analysera de grupprocesser som utvecklas mellan fyra unga män i en bil och att studera hur dessa interaktioner påverkar körbeteendet. Detta undersöktes med en observationsstudie där tolv unga män fick köra en instrumenterad bil i verklig trafik, både med och utan passagerare. Interaktionerna som uppstod i bilen spelades in med hjälp av videokameror och mikrofoner och körbeteendet registrerades med olika mätinstrument. Resultatet visar att förare med passagerare har en lägre olycksrisk jämfört med förare utan passagerare oavsett förarens ålder. Denna effekt är inte lika stark för unga förare (speciellt inte unga män) som den är för övriga åldersgrupper. Unga förares olyckor med passagerare är också mer vanligt förekommande under speciella omständigheter. Jämfört med olyckor utan passagerare sker de i större utsträckning under nattetid, under veckoslut, i tätbebyggt område, på vägar med hög hastighetsbegränsning, de är oftare singelolyckor och de får mer allvarliga konsekvenser. Vidare visar resultaten att passagerare ibland, på olika sätt, försöker få den unga föraren att köra på ett annat sätt än vad de gör vilket kan betyda ett säkrare eller ett mer trafikfarligt beteende. Det verkar dock som att förarna oftast står emot dessa övertalningsförsök och förolämpningar. En annan faktor som påverkar gruppen är kohesion: en hög grad av kohesion, speciellt uppgiftskohesion, visar sig leda till färre trafikfarliga körbeteenden. Med andra ord verkar det som att blotta närvaron av passagerare inte räcker för att få ett säkert körbeteende; det behövs även en betydande grad av kohesion.

This thesis presents the results of an investigation into the failure detection problem. We consider the specific case of the Quality of Service (QoS) of crash failure detection. In contrast to previous work, we address the crash failure detection problem when the monitored target is resilient and recovers after failure. To the best of our knowledge, this is the first work to provide an analysis of crash-recovery failure detection from the QoS perspective. We develop a probabilistic model of the behavior of a crash-recovery target, i.e. one which has the ability to recover from the crash state. We show that the fail-free run and the crash-stop run are special cases of the crash-recovery run with mean time to failure (MTTF) approaching to infinity and mean time to recovery (MTTR) approaching to infinity, respectively. We extend the previously published QoS metrics to allow the measurement of the recovery speed, and the definition of the completeness property of a failure detector. Then, the impact of the dependability of the crash-recovery target on the QoS bounds for such a crash-recovery failure detector is analyzed using general dependability metrics, such as MTTF and MTTR, based on an approximate probabilistic model of the two-process failure detection system. Then according to our approximate model, we show how to estimate the failure detector’s parameters to achieve a required QoS, based on Chen et al.’s NFD-S algorithm analytically, and how to execute the configuration procedure of this crash-recovery failure detector. In order to make the failure detector adaptive to the target’s crash-recovery behavior and enable the autonomy of the monitoring procedure, we propose two types of recovery detection protocols. One is a reliable recovery detection protocol, which can guarantee to detect each occurring failure and recovery by adopting persistent storage. The other is a lightweight recovery detection protocol, which does not guarantee to detect every failure and recovery but which reduces the system overhead. Both of these recovery detection protocols improve the completeness without reducing the other QoS aspects of a failure detector. In addition, we also demonstrate how to estimate the inputs, such as the dependability metrics, using the failure detector itself. In order to evaluate our analytical work, we simulate the following failure detection algorithms: the simple heartbeat timeout algorithm, the NFD-S algorithm and the NFDS algorithm with the lightweight recovery detection protocol, for various values of MTTF and MTTR. The simulation results show that the dependability of a recoverable monitored target could have significant impact on the QoS of such a failure detector. This conforms well to our models and analysis. We show that in the case of reasonable long MTTF, the NFD-S algorithm with the lightweight recovery detection protocol exhibits better QoS than the NFD-S algorithm for the completeness of a crash-recovery failure detector, and similarly for other QoS metrics.

nforme final de Seminario para optar al grado de Licenciada en Lengua y Literatura Hispánica con mención en Literatura / En este primer capítulo nos proponemos mostrar un panorama general acerca de la ciencia ficción (en adelante CF) y las problemáticas que pueden desprenderse de ella, para así tener una base sobre la cual instalar nuestros análisis personales de diferentes novelas del género. La primera parte del Seminario de Grado el curso se enfocó en abordar lo que más adelante expondremos, es decir, la historia del género, su definición, y sus distintas manifestaciones en subgéneros; para lo cual leímos y vimos varias o bras que resultan representativas de la CF. Además, se dedicó tiempo a procesar la bibliografía con la que trabajaremos, y a discutir distintos aspectos de la misma. Así, durante la segunda parte del curso, enfocada a la producción de nuestros informes fin ales, pudimos aplicar y ampliar lo visto en clases en función de la obra que cada uno decidió analizar. Antes de comenzar, es pertinente mencionar un suceso que tomó lugar tras asistir al primer encuentro de seminario de grado: nos enteramos de que todos manejamos un nivel de inglés que nos permite leer en el idioma. Este aspecto resultó relevante, pues la gran mayoría de las obras y bibliografía de ciencia ficción es producida por angloparlantes. Luego de llegar un acuerdo común, el profesor guía decidió reestructurar el programa del curso, en función de incluir textos actuales que carecen de traducciones. Tal decisión impactó nuestro paso por el seminario, pues el espectro de posibilidades para elegir nuestro objeto de estudio se vio favorablemente ampliado.

The stock market crash of 1929 stands today as the largest decline in market value in the history of the United States. Consequently, the event destroyed the wealth of thousands of American families and institutions. On October 28th and 29th, the United States stock market fell 11.3 percent and 12.4 percent respectively, marking the beginning of a down market that lasted over three years, the time period known today as the Great Depression. This paper empirically analyzes the effects felt by each individual industry sector in the crash of 1929, identifying gross and abnormal returns over three major days in the crash. I then compare my findings to previous literature and economic theories, analyzing which sector returns were expected and which were abnormal.