Performance characteristics and design recommendations for biomass-burning stoves using earthen construction materials

This report provides an analysis of the thermal performance and emissions characteristics of improved biomass stoves constructed using earthen materials. Commonly referred to as mud stoves, this type of improved stove incorporates high clay content soil with an organic binder in the construction of its combustion chamber and body. When large quantities of the mud material are used to construct the stove body, the stove does not offer significant improvements in fuel economy or air quality relative to traditional open fire cooking. This is partly because a significant amount of heat is absorbed by the mass of the stove reducing combustion efficiency and heat transfer to the cook pot. An analysis of the thermal and mechanical properties of stove materials was also performed. A material mixture containing a one‐to‐one ratio by volume of high content clay soil and straw was found to have thermal properties comparable to fired ceramics used in more advanced improved stove designs. Feedback from mud stove users in Mauritania and Mali, West Africa was also collected during implementation. Suggestions for stove design improvements were developed based on this information and the data collected in the performance, emissions, and material properties analysis. Design suggestions include reducing stove height to accommodate user cooking preferences and limiting overall stove mass to reduce heat loss to the stove body.

A 45nm CMOS DESIGN OF NEUROMORPHIC SYSTEM

Neuromorphic computing has become an emerging field in wide range of applications. Its challenge lies in developing a brain-inspired architecture that can emulate human brain and can work for real time applications. In this report a flexible neural architecture is presented which consists of 128 X 128 SRAM crossbar memory and 128 spiking neurons. For Neuron, digital integrate and fire model is used. All components are designed in 45nm technology node. The core can be configured for certain Neuron parameters, Axon types and synapses states and are fully digitally implemented. Learning for this architecture is done offline. To train this circuit a well-known algorithm Restricted Boltzmann Machine (RBM) is used and linear classifiers are trained at the output of RBM. Finally, circuit was tested for handwritten digit recognition application. Future prospects for this architecture are also discussed.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

Driver Safety in Far-side and Far-oblique Crashes: A Study of Patrol Vehicles in the United States of America

The dissertation titled "Driver Safety in Far-side and Far-oblique Crashes" presents a novel approach to assessing vehicle cockpit safety by integrating Human Factors and Applied Mechanics. The methodology of this approach is aimed at improving safety in compact mobile workspaces such as patrol vehicle cockpits. A statistical analysis performed using Michigan state's traffic crash data to assess various contributing factors that affect the risk of severe driver injuries showed that the risk was greater for unrestrained drivers (OR=3.38, p<0.0001) and for incidents involving front and far-side crashes without seatbelts (OR=8.0 and 23.0 respectively, p<0.005). Statistics also showed that near-side and far-side crashes pose similar threat to driver injury severity. A Human Factor survey was conducted to assess various Human-Machine/Human-Computer Interaction aspects in patrol vehicle cockpits. Results showed that tasks requiring manual operation, especially the usage of laptop, would require more attention and potentially cause more distraction. A vehicle survey conducted to evaluate ergonomics-related issues revealed that some of the equipment was in airbag deployment zones. In addition, experiments were conducted to assess the effects on driver distraction caused by changing the position of in-car accessories. A driving simulator study was conducted to mimic HMI/HCI in a patrol vehicle cockpit (20 subjects, average driving experience = 5.35 years, s.d. = 1.8). It was found that the mounting locations of manual tasks did not result in a significant change in response times. Visual displays resulted in response times less than 1.5sec. It can also be concluded that the manual task was equally distracting regardless of mounting positions (average response time was 15 secs). Average speeds and lane deviations did not show any significant results. Data from 13 full-scale sled tests conducted to simulate far-side impacts at 70 PDOF and 40 PDOF was used to analyze head injuries and HIC/AIS values. It was found that accelerations generated by the vehicle deceleration alone were high enough to cause AIS 3 - AIS 6 injuries. Pretensioners could mitigated injuries only in 40 PDOF (oblique) impacts but are useless in 70 PDOF impacts. Seat belts were ineffective in protecting the driver's head from injuries. Head would come in contact with the laptop during a far-oblique (40 PDOF) crash and far-side door for an angle-type crash (70 PDOF). Finite Element analysis head-laptop impact interaction showed that the contact velocity was the most crucial factor in causing a severe (and potentially fatal) head injury. Results indicate that no equipment may be mounted in driver trajectory envelopes. A very narrow band of space is left in patrol vehicles for installation of manual-task equipment to be both safe and ergonomic. In case of a contact, the material stiffness and damping properties play a very significant role in determining the injury outcome. Future work may be done on improving the interiors' material properties to better absorb and dissipate kinetic energy of the head. The design of seat belts and pretensioners may also be seen as an essential aspect to be further improved.

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.