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One dominant “wind noise” generating mechanism in road vehicles is the interaction between turbulent flows and flexible structures which include side glass windows. In this study, the effects of seal mechanical properties on the sound generated from flow-induced vibration of side glass windows were investigated. The primary goal was to assess the influence of seal support properties on the noise generated from a plate. Two different models to calculate the optimal support stiffness of the seal that minimizes the velocity response are presented. The results show that both the velocity response and the sound radiation are strongly influenced by dissipation of vibration energy at the edges. It is demonstrate that support tuning can yield significant noise and vibration reduction.

This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework.

An increase in the number of vehicles per capita coupled with stricter emission regulations have made the development of newer and better hybrid vehicle architectures indispensable. Although electric hybrids have more visibility and are now commercially available, hydraulic hybrids, with their higher power densities and cheaper components, have been rigorously explored as the alternative. Several architectures have been proposed and implemented for both on and off highway applications. The most commonly used architecture is the series hybrid, which requires an energy conversion from the primary source (engine) to the secondary domain. From he re, the power flows either into the secondary source (high-pressure accumulator) or to the wheels depending upon the state of charge of the accumulator. A mode-switching hydraulic hybrid, which is a combination of a hydrostatic transmission and a series hybrid, was recently developed in the author’s research group.

Resource recovery, including that of urine water extraction, is one of the most crucial aspects of long-term life support in interplanetary space travel. This paper will consequently examine an innovative approach to processing raw, undiluted urine based on low-temperature freezing. This strategy is uniquely different from NASA's current emphasis on either ‘integrated’ (co-treatment of mixed urine, grey, and condensate waters) or ‘high-temperature’ (i.e., VCD [vapor compression distillation] or VPCAR [vapor phase catalytic ammonia removal]) processing strategies, whereby this liquid freeze-thaw (LiFT) procedure would avoid both chemical and microbial cross-contamination concerns while at the same time securing highly desirable reductions in likely ESM levels.

As part of the NASA Specialized Center of Research and Training for Advanced Life Support (NSCORT-ALS) at Purdue University, a complementary disinfection process, which uses ultraviolet (UV) radiation as the primary disinfectant and iodine as the secondary, residual disinfectant, is being developed. UV radiation was selected as the primary disinfectant because it is effective at inactivating a broad spectrum of microorganisms and has minimal potential for the formation of disinfection byproducts. Iodine, which is effective at inactivating many microorganisms and is less likely to react and form disinfection byproducts than other halogens, was selected as the residual disinfectant because it has the potential for dual use as an on-line UV monitor, as well as a disinfectant.

Modern on-road vehicles have been making steady strides when it comes to employing technological advances featuring active safety systems. However, off-highway machines are lagging in this area and are in dire need for modernization. One chassis system that has been receiving much attention in the automotive field is the steering system, where several electric and electrohydraulic steering architectures have been implemented and steer-by-wire technologies are under current research and development activities. On the other hand, off-highway articulated steering vehicles have not adequately evolved to meet the needs of Original Equipment Manufacturers (OEM) as well as their end customers. Present-day hydrostatic steering systems are plagued with poor energy efficiency due to valve throttling losses and are considered passive systems relative to safety, adjustability, and comfort.

Spherical beamforming was used to visualize sound radiation during a vehicle passby test. Forward and backward propagation procedures are compared in terms of computational expense. A spherical spreading correction factor is described, along with a maximum liklihood procedure for obtaining an optimal array weighting dependent on the relative distance between the microphones and the focus point. The de-Dopplerized microphone outputs are multiplied by the weighting factors and summed to yield the source strengths over a reconstruction plane “attached” to the vehicle. Results obtained using a 16 element sparse array during an actual passby are used to demonstrate the present approach.

An overview of model development for seated occupants is presented. Two approaches have been investigated for modeling the vertical response of a seated dummy: finite element and simplified mass-spring-damper methods. The construction and implementation of these models are described, and the various successes and drawbacks of each modeling approach are discussed. To evaluate the performance of the models, emphasis was also placed on producing accurate, repeatable measurements of the static and dynamic characteristics of a seated dummy.

The design optimization of thin-walled tubular structures is of relevance in the automotive industry due to their low cost, ease of manufacturing and installation, and high-energy absorption efficiency. This study presents a methodology to design thin-walled tubular structures for crashworthiness applications. During an impact, thin-walled tubular structures may exhibit progressive collapse/buckling, global collapse/buckling, or mixed collapse/buckling. From a crashworthiness standpoint, the most desirable collapse mode is progressive collapse due to its high-energy absorption efficiency, stable deformation, and low peak crush force (PCF). In the automotive industry, thin-walled components have complex structural geometries. These complexities and the several loading conditions present in a crash reduce the possibility of progressive collapse. The Hybrid Cellular Automata (HCA) method has shown to be an efficient continuum-based approach in crashworthiness design.

Structures with multiple materials have now become one of the perceived necessities for automotive industry to address vehicle design requirements such as light-weight, safety, and cost. The objective of this study is to develop a design methodology for multi-material structures accountable for vehicle crash durability. The heuristic topology synthesis approach of Hybrid Cellular Automaton (HCA) framework is implemented to generate multi-material structures with the constraint on the volume fraction of the final design. The HCA framework is integrated with ordered-SIMP (solid isotropic material with penalization) interpolation, artificial material library, as well as statistical analysis of material distribution data to ensure a smooth transition between multiple practical materials during the topology synthesis.

The formation of ice on aircraft is a highly dynamic process during which ice will expand and contract upon freezing and undergoing changes in temperature. Finite element analysis (FEA) simulations were performed investigating the stress/strain response of an idealized ice sample bonded to an acrylic substrate subjected to a uniform temperature change. The FEA predictions were used to guide the placement of strain gages on custom-built acrylic and aluminum specimens. Tee rosettes were placed in two configurations adjacent to thermocouple sensors. The specimens were then placed in icing conditions such that ice was grown on top of the specimen. It was hypothesized that the ice would expand on freezing and contract as the temperature of the interface returned to the equilibrium conditions.

This paper introduces a design methodology to tailor the acceleration and displacement responses of a vehicle structure subjected to a dynamic crushing load. The proposed approach is an extension of the hybrid cellular automaton (HCA) method, through which the internal energy density is uniformly distributed within the structure. The proposed approach, referred here to as an extended HCA (xHCA) method, receives the suitable combinations of volume fraction and a finite element meta-parameter for which the algorithm synthesizes the load paths that allow the desired crash response. Lower meta-parameter values lead designs obtained by traditional optimizers, while larger values lead to designs obtained by the HCA method. Simultaneous implementation of multiple values of meta-parameters is presented here as a further development of xHCA method.

A common scenario in engineering design is the evaluation of expensive black-box functions: simulation codes or physical experiments that require long evaluation times and/or significant resources, which results in lengthy and costly design cycles. In the last years, Bayesian optimization has emerged as an efficient alternative to solve expensive black-box function design problems. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition functions that drives the design process. Successful Bayesian optimization strategies are characterized by accurate surrogate models and well-balanced acquisition functions. The Gaussian process (GP) regression model is arguably the most popular surrogate model in Bayesian optimization due to its flexibility and mathematical tractability. GP regression models are defined by two elements: the mean and covariance functions.

In the dense fabric of urban areas, electric scooters have rapidly become a preferred mode of transportation. As they cater to modern mobility demands, they present significant safety challenges, especially when interacting with pedestrians. In general, e-scooters are suggested to be ridden in bike lanes/sidewalks or share the road with cars at the maximum speed of about 15-20 mph, which is more flexible and much faster than pedestrians and bicyclists. Accurate prediction of pedestrian movement, coupled with assistant motion control of scooters, is essential in minimizing collision risks and seamlessly integrating scooters in areas dense with pedestrians. Addressing these safety concerns, our research introduces a novel e-Scooter collision avoidance system (eCAS) with a method for predicting pedestrian trajectories, employing an advanced Long short-term memory (LSTM) network integrated with a state refinement module.