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Driveline and suspension notched components of off-road ground vehicles often experience multiaxial fatigue failures along notch locations. Large nominal load histories may induce local elasto-plastic stress and strain responses at the critical notch locations. Fatigue life prediction of such notched components requires detailed knowledge of local stresses and strains at notch regions. The notched components that are often subject to multiaxial loadings in services, experience complex stress and strain responses. Fatigue life assessment of the components utilizing non-linear Finite Element Analysis (FEA) require unfeasibly inefficient computation times and large data. The lack of more efficient and effective methods of elasto-plastic stress-strain calculation may lead to the overdesign or earlier failures of the components or costly experiments and inefficient non-linear FEA.

In the cockpit of NASA's next generation spacecraft, most vehicle command will be performed via electronic interfaces instead of hard cockpit switches. Checklists will be also displayed and completed on electronic procedure viewers rather than on paper. Transitioning to electronic cockpit interfaces opens up opportunities for more automated assistance, including automated root-cause diagnosis capability. The paper reports an empirical study evaluating two potential concepts for fault management interfaces incorporating two different levels of automation. The operator performance benefits produced by automation were assessed. Also, some design recommendations for spacecraft fault management interfaces are discussed.

Since the mid 1980s, NASA has developed advanced waste management technologies that collect and process waste. These technologies include incineration, hydrothermal oxidation, pyrolysis, electrochemical oxidation, activated carbon production, brine dewatering, slurry bioreactor oxidation, composting, NOx control, compaction, and waste collection. Some of these technologies recover resources such as water, oxygen, nitrogen, carbon dioxide, carbon, fuels, and nutrients. Other technologies such as the Waste Collection System (WCS - the commode) collect waste for storage or processing. The need for waste processing varies greatly depending upon the mission scenario. This paper reviews the waste management technology development activities conducted by NASA since the mid 1980s and explores the drivers that determine the application of these technologies to future missions.

In February 2004 NASA released “The Vision for Space Exploration.” The goals outlined in this document include extending the human presence in the solar system, culminating in the exploration of Mars. A key requirement for this effort is to identify a safe and effective method to process waste. Methods currently under consideration include incineration, microbial oxidation, pyrolysis, drying, and compaction. Although each has advantages, no single method has yet been developed that is safe, recovers valuable resources including oxygen and water, and has low energy and space requirements. Thus, the objective of this work is to develop a low temperature oxidation process to convert waste cleanly and rapidly to carbon dioxide and water. Previously, TDA Research, Inc. demonstrated the potential of a low temperature dry oxidation process using ozone in a small laboratory reactor.

The Lightweight Contingency Water Recovery System (LWC-WRS) harvests water from various sources in or around the Orion spacecraft in order to provide contingency water at a substantial mass savings when compared to stored emergency water supplies. The system uses activated carbon treatment (for urine) followed by forward osmosis (FO). The LWC-WRS recovers water from a variety of contaminated sources by directly processing it into a fortified (electrolyte and caloric) drink. Primary target water sources are urine, seawater, and other on board vehicle waters (often referred to as technical waters). The product drink provides hydration, electrolytes, and caloric requirements for crew consumption. The system hardware consists of a urine collection device containing an activated carbon matrix (Stage 1) and an FO membrane treatment element (or bag) which contains an internally mounted cellulose triacetate membrane (Stage 2).

Due to the instabilities that may occur in power systems with regulated loads such as those used in military aircraft, ships, and terrestrial vehicles, many analysis techniques and design methodologies have been developed to ensure stable operation for expected operating conditions. However, many of these techniques are difficult to apply to complex systems and do not guarantee large-displacement stability following major disturbances such as faults, regenerative operation, large pulsed loads, and/or the loss of generating capacity. In this paper, a design paradigm is set forth guaranteeing large-displacement stability of a power system containing a significant penetration of regulated (constant-power) loads for any value of load power up to and including the steady-state rating of the source. Initial investigations are performed using an idealized model of a dc-source to determine the minimum requirements that ensure large-displacement stability.

Noise generation in axial piston machines can be attributed to two main sources; fluid borne and structure borne. Any attempt towards noise reduction in axial piston machines should focus on simultaneous reduction of these two sources. A multi-parameter multi-objective optimization approach to design valve plates to reduce both sources of noise for pumps which operate in a wide range of operating conditions has been detailed in a previous work (Seeniraj and Ivantysynova, 2008). The focus of this paper is to explain the background and to demonstrate the functionality and usefulness of the methodology for pump design.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.

The cost and complexity of aircraft power systems limit the number of integrated system evaluations that can be performed in hardware. As a result, evaluations are often performed using emulators to mimic components or subsystems. As an example, aircraft generation systems are often tested using an emulator that consists of a bank of resistors that are switched to represent the power draw of one or more actuators. In this research, consideration is given to modern wide bandwidth emulators (WBEs) that use power electronics and digital controls to obtain wide bandwidth control of power, current, or voltage. Specifically, this paper first looks at how well a WBE can emulate the impedance of a load when coupled to a real-time model. Capturing the impedance of loads and sources is important for accurately assessing the small-signal stability of a system.

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.

Shell-and-tube heat exchangers, commonly referred to as radiators, are the most prevalent type of heat exchanger within the automotive industry. A pivotal goal for automotive designers is to increase their thermal effectiveness while mitigating pressure drop effects and minimizing the associated costs of design and operation. Their design is a lengthy and intricate process involving the manual creation and refinement of computer-aided design (CAD) models coupled with iterative multi-physics simulations. Consequently, there is a pressing demand for an integrated tool that can automate these discrete steps, yielding a significant enhancement in overall design efficiency. This work aims to introduce an innovative automation tool to streamline the design process, spanning from CAD model generation to identifying optimal design configurations. The proposed methodology is applied explicitly to the context of shell-and-tube heat exchangers, showcasing the tool's efficacy.

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.

This paper describes a psychoacoustic test in the Exterior Effects Room (EER) at the NASA Langley Research Center. The test investigated the degree to which sound quality metrics (sharpness, tonality, etc.) are predictive of annoyance to notional sounds of Urban Air Mobility (UAM) vehicles (e.g., air taxis). A suite of 136 unique (4.6 second duration) UAM rotor noise stimuli was generated. These stimuli were based on aeroacoustic predictions of a NASA reference UAM quadrotor aircraft under two flight conditions. The synthesizer changed rotor noise parameters such as the blade passage frequency, the relative level of broadband self-noise, and the relative level of tonal motor noise. With loudness constant, the synthesis parameters impacted sound quality in a way that created a spread of predictors both in synthesizer parameters and in sound quality metrics.

Layered materials are one of the most commonly used acoustical treatments in the automotive industry, and have gained increased attention, especially owing to the popularity of electric vehicles. Here, a method to model and couple layered systems with various layer types (i.e., poro-elastic layers, solid-elastic layers, stiff panels, and fluid layers) is derived that makes it possible to stably predict their acoustical properties. In contrast with most existing methods, in which an equation system is constructed for the whole structure, the present method involves only the topmost layer and its boundary conditions at two interfaces at a time, which are further simplified into an equivalent interface. As a result, for a multi-layered system, the proposed method splits a complicated system into several smaller systems and so becomes computationally less expensive.

As the vehicle and wind speeds and directions change, the unsteady flow creates non-stationary wind noise. To investigate people’s perceptions of non-stationary wind noise, a method to simulate the non-stationary wind noise is needed. Previously, a method was developed that used stationary recordings taken at several speeds and directions to create a set of sound pressure level predictions in each one-third octave band that are a function of wind speed and direction. These functions are used to create time-varying filters based on provided wind profiles. A reference wind noise measurement is then filtered to produce the sounds. A drawback of this method is that many stationary wind condition measurements are needed to form accurate sound pressure level functions, which can be time consuming. A method requiring fewer measurements was investigated.