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The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

This paper presents a method for indirect measurement of tire slip angles from chassis acceleration, yaw rate, and steer angle measurements. The chassis is assumed to be rigid so that acceleration data can be integrated to estimate velocities of the front and rear of the vehicle, from which slip angles can be predicted. The difference in front and rear slip angles is indicative of vehicle oversteer/understeer. Understeer data can then be correlated with position on the track to better understand vehicle handling behavior, aiding the tuning process. The technique is presented, and shown to work well with simulated data, even when the data is corrupted with up to 20% noise. Therefore, the inversion process presented here is theoretically sound. However, when the technique is applied to measured data from race cars, it is shown to be inaccurate. One suspected problem is the difficulty of getting accurate yaw rate data.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.

There has always been, from the very first UAV, a need for providing cost-effective methods of deploying unmanned aircraft systems at high altitudes. Missions for UAVs at high altitudes are used to conduct atmospheric research, perform global mapping missions, collect remote sensing data, and establish long range communications networks. The team of Gevers Aircraft, Technology Management Group, and Purdue University have designed an innovative balloon launched UAV for these near space applications. A UAV (Payload Return Vehicle) with a nested morphing wing was designed in order to meet the challenges of high altitude flight, and long range and endurance without the need for descent rate control with rockets or a feathering mode.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

Operation & support costs for military weapon systems accounted for approximately 3/5th of the $500B Department of Defense budget in 2006. In an effort to ensure readiness and decrease these costs for ground vehicle fleets, health monitoring technologies are being developed for Condition-Based Maintenance of individual vehicles within a fleet. Dynamics-based health monitoring is used in this work because vibrations are a passive source of response data, which are global functions of the mechanical loading and properties of the vehicle. A common way of detecting faults in mechanical equipment, such as the suspension and chassis of a ground vehicle, is to compare measured operational vibrations to a reference (or healthy) signature to detect anomalies.

This paper describes the numerical modeling of the hydraulic circuit of a self-moving boom lift. Boom lifts consist of several hydraulic actuators, each of them performs a specific movement. Hydraulic systems for lifting applications must ensure consistent performance no matter what the load and how many users are in operation at the same time. Common solutions comprise a fixed or a variable displacement pump with load-sensing control strategy. Instead, the hydraulic circuit studied in this paper includes a fixed displacement pump and an innovative (patented) proportional valve assembly. Each proportional valve (one for each user) permits a flow regulation for all typical load conditions and movement simultaneously. The study of the hydraulic system required a detailed modeling of some components such as: the overcenter valves, for the control of the assistive loads; the proportional valve, which keeps a constant flow independently of pressure drop across itself.

A methodology for modeling elastomeric mounts as nonlinear lumped parameter models is discussed. A key feature of this methodology is that it integrates dynamic test results under different conditions into the model. The first step is to model the mount as a linear model that is simple but reproduces accurately results from dynamic tests under small excitations. Frequency Response Functions (FRF) enables systematic calculation of the parameters for the model. Under more realistic excitation, the mount exhibits non-linearity, which is investigated in the next step. For nonlinear structures, a simple and intuitive method is to use time-domain force-displacement (F-x) curves. Experiments to obtain the F-x curves involve controlling the displacement excitation and measuring the induced forces. From the F-x curves, stiffness and damping parameters are obtained with an optimization technique.

This paper presents the continuation of the modeling work described in a companion paper “Modeling of Nonlinear Elastomeric Mounts. Part 1: Dynamic Testing and Parameter Identification” by the same authors. That paper discussed a dynamic test procedure and an optimization methodology to identify and model an elastomeric mount as a non-linear lumped parameter structure. This paper discusses a numerical modeling methodology to confirm or improve the agreement between the dynamic test results and the input-output relationship of the analytical model generated in the companion paper. In this paper, the model developed in the companion paper and the model parameters are input into a dynamic simulation model using a commercial simulation package. The model is then run to produce the numerical force-versus-displacement (F-x) curves of the mount. The numerical F-x curves are compared with the F-x curves obtained from the experiments.

Design optimization for functionality, and manufacturability was virtually impossible in the past. However, recent standardization of file storing formats resulted in seamless data transfer from one software package to another; thus, allowing integration of all facets of product design optimization. This paper describes a metalcasting design optimization process. It focuses on the design of cast parts according to functional requirements while optimizing shape with respect to structural integrity, while ascertaining that the part can be manufactured (cast) without defects.

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.

This work presents the implementation of the Efficient Global Optimization (EGO) approach for the design of composite materials under dynamic loading conditions. The optimization algorithm is based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design towards a global optimum. An expected improvement function is maximized during each iteration to locate the designs that update the metamodel until convergence. The algorithm solves single and multi-objective optimization problems. In the first case, the penetration of an armor plate is minimized by finding the optimal fiber orientations. Multi-objective formulation is used to minimize the intrusion and impact acceleration of a composite tube. The design variables include the fiber orientations and the size of zones that control the tube collapse.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

The ALS/NSCORT Education and Outreach provides an avenue to engage and educate higher education students and K-12 educators/students in the center's investigations of the synergistic concepts and principles required for regenerative life-support in extended-duration space exploration. The following K-12 Education programs will be addressed: 1) Key Learning Community Project provides exposure, mentoring and research opportunities for 9-12th grade students at Key Learning Community This program was expanded in 2004 to include an “Explore Mars” 3-day camp experience for 150 Key students. The overall goal of the collaborative project is to motivate students to pursue careers in science, technology, and engineering; 2) Mission to Mars Program introduces 5th-8th grade students to the complex issues involved with living on Mars, stressing the interdisciplinary fundamentals of science, technology and engineering that underlie Advanced Life Support research.

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.

The application of biological treatment to solid waste is very promising to facilitate recycling of water, carbon, and nutrients and to reduce the resupply needs of long-term crewed space missions. Degradation of biodegradable solid wastes generated during such a mission is under investigation as part of the NASA Center of Research and Training (NSCORT) at Purdue University. Processing in the solids thermophilic aerobic reactor (STAR) involves the use of high temperature micro-aerobic slurry conditions to degrade solid wastes, enabling the recycling of water, carbon, and nutrients for further downstream uses. Related research presently underway includes technical development and optimization of STAR operations as well as a complementary evaluation of post-STAR processing for gas-stream purification, water recovery by condensate purification, and residuals utilization for both mushroom growth media and nutritional support for fish growth.

The NASA Specialized Center of Research and Training in Advanced Life Support (ALS/NSCORT) Education and Outreach Program is designed to engage audiences through concepts and technologies highlighted in the NSCORT research program. The outreach program is composed of three thrust areas. These areas are technical outreach (graduate education, technology transfer, presentations to industry, etc.), educational outreach (professional development, undergraduate, K-12), and public outreach (museums, state fairs, etc.) Program design of the technical and educational outreach began in January 2003. This paper reports anecdotal data on one ALS/NSCORT outreach program and gives a brief description of the other programs in their pilot stages. Technical and educational outreach programs developed to date include: 1) Summer Fellowship Research Program, 2) Distance Learning Course, 3) Key Learning Community Collaborative Project and 4) Mission to Mars.

Solids thermophilic aerobic reactor (STAR) processing of biodegradable solid waste residuals uses high temperature conditions to reduce waste volume, inactivate pathogens, and render products that may enter the recycle system by providing plant substrate, fish food, and mushroom growth medium. The STAR process recovers and enables the reuse of nutrients, water, and carbon. During the time of this study, STAR was operated at a 3% solids loading rate, with an 11-day retention time at a temperature range of 50-55°C. This document presents the following details: a the evolution to date of the STAR reactor b review of reactor operation and analytical methods c a synopsis of the performance results and related discussion, and d a synopsis of future goals relative to this project's associated research roadmap.