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Aircraft survivability is a classical consideration of combat aircraft design and tactical development, but the fundamental model of aircraft survivability must be updated to be able to consider modern tactical scenarios that are applicable to unmanned aircraft. This paper seeks therefore to define the set of design tradeoffs and an evaluation of the tactical effectiveness for unmanned aircraft survivability. Traditional and modern survivability evaluation methods are presented and integrated into a computational simulation to create a probabilistic evaluation of unmanned aircraft survivability. The results demonstrate the development of design tradeoffs for a hypothetical unmanned C-130J Hercules against a single man-portable air defense system. The discussion focuses on the demonstration of the utility of this survivability evaluation framework for consideration of survivability in unmanned aerial vehicle (UAV) design, the utility of considering survivability in the design of multi-UAV configurations (including the loyal wingman and swarms), and the value of the probabilistic survivability model for multi-aircraft simulations.

This study seeks to compare the quantity of information that is automatically transferred through the associations generated using a model-based systems engineering (MBSE) approach versus a traditional systems engineering approach to measure the benefits of MBSE in architecting a robotic space system. Both an MBSE approach and non-MBSE approach were applied to architecting an orbiting sample Capture and Orient Module (COM) system concept for a Capture, Containment, and Return System (CCRS) payload concept for Mars Sample Return (MSR). These approaches were applied in parallel to provide a side-by-side comparison of the approaches. The approaches were analyzed using design structure matrices (DSM) and evaluated based on the amount of information transferred between process tasks manually (e.g., elements physically typed into text boxes in a presentation slide) vs automatically (e.g., elements automatically filled out within a block in a model view due to explicitly defined element associations). A total of 4,819 information element transfers were traced in DSMs and used to quantitatively compare the two approaches. The non-MBSE approach required manual transfer for all 4,819 information elements. The MBSE approach required manual transfer for 4,189 information elements and automatic transfer for 630 information elements, providing a minor increase in the automation of information transfer relative to the non-MBSE approach. By incorporating the use of additional MBSE artifacts into the trade study and peer review tasks, manual transfer could potentially be reduced to 931 information elements, and automatic transfer increased to 3,888 information elements.

The increasing number of Electronic Control Units (ECUs) in today's vehicles and their greater connectivity with the outside environment has made vehicles more vulnerable to security attacks. Integrating security mechanisms in ECUs has become essential, but incurs overheads, which can delay safety-critical task execution and message transfers. In this work, we introduce a methodology to derive security requirements for tasks and messages in automotive systems based on the ISO 26262 standard. We then propose a framework ( SEDAN ) to increase the security of the system without violating the real-time constraints and security requirements of messages, or ECU utilization limits.

Hydrogen infrastructure for fueling vehicles has progressed in the last decade from stations with restricted access and limited operating hours to customer-friendly retail stations open to the public. There are now 121 retail hydrogen stations around the world. In California, the number of public retail hydrogen stations has increased from zero to more than 30 in less than two years, and the annual amount of hydrogen dispensed by retail stations has grown from 27,400 kg in 2015 to nearly 105,000 kg in 2016 and more than 440,000 kg in 2017—an increase of about four times year over year. For more than a decade, government, industry, and academia have studied many aspects of hydrogen infrastructure, from renewable hydrogen production to retail hydrogen station performance. This paper reviews the engineering and deployment of modern hydrogen infrastructure, including the costs, benefits, and operational considerations (including safety, reliability, availability), as well as challenges to the scale-up of hydrogen infrastructure. The results identify hydrogen station reliability as a key factor in the expense of operating hydrogen systems, placing it in the context of the larger reliability engineering field.

In-motion charging of electric vehicles (EVs) using wireless power transfer (WPT) represents an alternative to both traditional internal combustion engine (ICE) transportation and long-range EVs. This paper focuses on understanding the economics, environmental impact, and infrastructure rollout of in-motion WPT applied to the U.S. transportation fleet. This paper represents a novel, large-scale integration of numerous research methodologies previously presented by our research group into a comprehensive study to thoroughly address potential in-motion WPT implementation scenarios using geographically diverse data sets, validated vehicle models, real-world drive cycles, variable vehicle adoption rates, and variable infrastructure deployment rates. By using both in-motion WPT and conventional charging infrastructure, the proposed vehicle and roadway architectures satisfy 97.7% of the sampled 24-h drive cycles, a 22.4% increase over a baseline short-range EV without in-motion charging. Economic results show a national return on investment but economic viability is dramatically impacted by upfront capital costs and technology adoption. An environmental impact assessment shows that total greenhouse gas emissions from light-duty vehicles and Class 8 trucks would be reduced by 29.3 trillion kg CO2-eq. (30.6%) when compared to a business as usual scenario (i.e., a scenario were current overall emissions trends continue) for the first 50 years of technology deployment. These results demonstrate that in-motion charging using WPT presents both economic and environmental benefits when compared to conventional ICE transportation and a long-range EV fleet.

Electric vehicle (EV) charging infrastructure is present all over the United States, but charging prices vary greatly, both in amount and in the methods by which they are assessed. For this paper, we interpret and analyze charging price information from PlugShare, a crowd-sourced EV charging data platform. Because prices in these data exist in a semi-structured textual format, an ad hoc text mining approach is used to extract quantitative price information. Descriptive analytics of the processed dataset demonstrate how the prices of EV charging vary with charging level (Direct Current Fast Charging versus Level 2), geographic location, network provider, and location type. Our research indicates that a great deal of diversity and flexibility exists in structuring the prices of EV charging to enable incentives for shaping charging behaviors, but that it has yet to be widely standardized or utilized. Comparisons with estimates of the levelized cost of EV charging illustrate some of the challenges associated with operating and using these stations.

The use of new vehicle technologies such as fuel cell hybrid electric and fully electric powertrains for biomass feedstock supply is an unexplored solution to reducing biofuel production cost, greenhouse gas emissions, and health impacts. These technologies have found success in light-duty vehicle applications and are in development for heavy-duty trucks. This study presents the first detailed stochastic techno-economic analysis and life-cycle assessment of biomass feedstock supply systems with diesel, fuel cell hybrid electric, and fully electric trucks and determines their impacts on biofuel production considering butanol as a representative biofuel. This study finds that fuel cell hybrid electric and fully electric trucks consume less energy relative to the diesel-powered truck regardless of the evaluated circumstances, including payloads of truck (loaded and empty), pavement types (gravel and paved), road conditions (normal and damaged), and road networks (local and highways). The use of fuel cell hybrid and fully electric trucks powered by H2-fuel and renewable sources of electricity, respectively, results in a large reduction in cost and carbon footprint, specifically for a long-distance hauling, and minimize other economic and environmental impacts. While the economic advantage of fuel cell hybrid electric vehicle is dependent on the price of H2-fuel and road conditions, use reduces the GHG emissions of biobutanol per 100 km-trucking-distance by 0.98–10.9 gCO2e/MJ. Results show that converting to fully electric truck transport decreases the biobutanol production cost and GHG emissions per 100 km-trucking-distance by 0.4–7.3 cents/L and 0.78 to 9.1 gCO2e/MJ, respectively. This study establishes the foundation for future investigations that will guide the development of economically, socially, and environmentally sustainable biomass feedstock supply system for cellulosic biorefineries or other goods transportation systems.

This study proposes a novel integration of a municipal wastewater treatment facility (WWTF) with a cyanobacterial nutrient removal process for sidestream wastewater treatment. A life cycle assessment (LCA) approach was used to determine the effectiveness and environmental performances of the integrated system. The LCA is populated by models of wastewater process engineering, material balance, cyanobacterial growth, and kinetics of anaerobic digestion. The cyanobacteria growth model incorporates chlorophyll synthesis, nitrogen uptake, photosynthesis, centrate inhibition, and competition for nitrogen between cyanobacteria and nitrifiers. Modeling results are validated against experiments with Synechocystis sp. PCC6803 grown in sludge centrate. With a maximum specific growth rate of 1.09 day−1, the nitrogen removal rate of the proposed WWTF would be increased by 15% when compared to the baseline wastewater treatment facility with a biological nutrient removal process. Incorporating the cyanobacterial nutrient removal process as the sidestream wastewater treatment of a conventional activated sludge process reduces the total nitrogen concentrations discharged from the WWTF from 25.9 to 15.2 mg 1−1. Methane yield was found to be increased by 4% of the baseline value when cyanobacterial biomass was co-digested with the activated sludge. Life cycle energy use and greenhouse gas emissions were found to be reduced by 8% and 17%, respectively, relative to a baseline wastewater treatment facility. Overall, a cyanobacteria-based sidestream municipal wastewater treatment process could be an effective and environmentally sustainable biological nutrient removal process in the future addressing the water-energy-food nexus.

Widely published research shows that significant fuel economy improvements through optimal control of a vehicle powertrain are possible if the future vehicle velocity is known and real-time optimization calculations can be performed. In this research, however, we seek to advance the field of optimal powertrain control by limiting future vehicle operation knowledge and using no real-time optimization calculations. We have realized optimal control of acceleration events (AEs) in real-time by studying optimal control trends across 384 real world drive cycles and deriving an optimal control strategy for specific acceleration event categories using dynamic programming (DP). This optimal control strategy is then applied to all other acceleration events in its category, as well as separate standard and custom drive cycles using a look-up table. Fuel economy improvements of 2% average for acceleration events and 3.9% for an independent drive cycle were observed when compared to our rigorously validated 2010 Toyota Prius model. Our conclusion is that optimal control can be implemented in real-time using standard vehicle controllers assuming extremely limited information about future vehicle operation is known such as an approximate starting and ending velocity for an acceleration event.

Advanced driver-assistance systems (ADASs) have become a salient feature for safety in modern vehicles. They are also a key underlying technology in emerging autonomous vehicles. State-of-the-art ADASs are primarily vision based, but light detection and ranging (lidar), radio detection and ranging (radar), and other advanced-sensing technologies are also becoming popular. In this article, we present a survey of different hardware and software ADAS technologies and their capabilities and limitations. We discuss approaches used for vision-based recognition and sensor fusion in ADAS solutions. We also highlight challenges for the next generation of ADASs.

The fuel cell plug in hybrid electric vehicle (FCPHEV) is a near-term realizable concept to commercialize hydrogen fuel cell vehicles (FCV). Relative to conventional FCVs, FCPHEVs seek to achieve fuel economy benefits through the displacement of hydrogen energy with grid-sourced electrical energy, and they may have less dependence on a sparse hydrogen fueling infrastructure. Through the simulation of almost 690,000 FCPHEV trips using geographic information system (GIS) data surveyed from a fleet of private vehicles in the Puget Sound area of Washington State, USA, this study derives the electrical and hydrogen energy consumption of various design and control variants of FCPHEVs. Results demonstrate that FCPHEVs can realize hydrogen fuel consumption reductions relative to conventional FCV technologies, and that the fuel consumption reductions increase with increased charge depleting range. In addition, this study quantifies the degree to which FCPHEVs are less dependent on hydrogen fueling infrastructure, as FCPHEVs can refuel with hydrogen at a lower rate than FCVs. Reductions in hydrogen refueling infrastructure dependence vary with control strategies and vehicle charge depleting range, but reductions in fleet-level refueling events of 93% can be realized for FCPHEVs with 40 miles (60 km) of charge depleting range. These fueling events occur on or near the network of highways at approximately 4% of the rate (refuelings per year) of that for conventional FCVs. These results demonstrate that FCPHEVs are a type of FCV that can enable an effective and concentrated hydrogen refueling network.

Anaerobic digestion is a well-known and potentially beneficial process for rural communities in emerging markets, providing the opportunity to generate usable gaseous fuel from waste resources. With recent developments in low-cost digestion technology, communities across the world are gaining affordable access to the benefits of anaerobic digestion derived biogas. For example, biogas provides a more efficient and cleaner burning alternative to biomass (wood, charcoal, dung), effectively reducing harmful emissions and fuel consumption. This study sought to develop and test a design approach for optimizing flame port geometry for household biogas-fired burners. The approach consists of a multi-component simulation that incorporates three-dimensional CAD designs with simulated chemical kinetics and computational fluid dynamics. The simulated flame port designs included an array of circular and rectangular geometries using a widely available biogas burner. The three highest performing designs identified were manufactured and tested experimentally to validate model outputs and to compare against a baseline port geometry. In the experiment, each of the three designs suggested improved thermal efficiency relative to the baseline. A configuration of four millimeter circular ports resulted in a 7.17% improvement, raising an average thermal efficiency of 53.0% to 56.8%. The results indicated that hydraulic diameter, velocity and mixture density are relevant factors in port geometry design to improve the thermal efficiency of a biogas burner. Conversely, the emissions predictions made by the model were found to be unreliable and incongruent with laboratory experiments.

Unconventional oil and gas (UOG) production requires a vast quantity of freshwater while generating substantial volumes of wastewater. Although numerous studies have focused on technology development, other aspects beyond treatment technology, including regulations, economics, system logistics, and public perception, play equally or more important roles collectively in the selection and deployment of UOG wastewater management practices. In this article, we begin with a critical analysis of the motivations that drive UOG wastewater management towards treatment and reuse. Then we examine four main barriers against such a paradigm shift, pertaining to treatment technology, regulatory compliance, economic feasibility, and social acceptance. Despite the need of further improving technology efficiency for UOG wastewater treatment, the lack of established regulatory framework, the uncertainties of economic viability, as well as public resistance, hinder practical implementation of treatment technologies. We highlight the importance of knowledge and collaborative efforts from engineers, regulators, policy makers, economists, and social scientists to address those barriers, and emphasize that future research efforts should be directed at domains well beyond treatment technology. A systems approach and broader collaboration across multiple disciplines is needed to translate technology innovation into solutions that truly improve water sustainability in the context of rising UOG production.

The net energy ratios (NERs) and greenhouse gas (GHG) emissions of a Photosynthetic Cyanobacterial Biorefinery (PSBR) were evaluated using a Life Cycle Assessment (LCA) approach. This study assessed engineered cyanobacterium cultures in which biosynthetic biofuels are directly secreted. Biofuels researched in this study include bisabolane, a biosynthetic substitute for D2 diesel; heptadecane, a substitute for diesel; and ethanol, a substitute for gasoline. Results demonstrate that cyanobacteria-based ethanol has higher yields, lower NER, and lower GHG emissions than bisabolane and heptadecane products in Synechocystis sp. PCC6803. By performing a sensitivity analyses of the life cycle NER and GHG emissions responses of the system, we derived the improvements in system biology, metabolic engineering, and process engineering that would be required to minimize the environmental impacts at an industrial scale. The NER and GHG emissions of the biofuel products were found to be the most sensitive to organism-level biofuel productivities, the energy consumption of vapor compression and distillation, and the energy consumption of culture mixing. This LCA will serve as a baseline for stakeholders; including policy makers, cyanobacterial refineries, and researchers, to establish the goals to engineer cyanobacteria and sustainable bioprocesses.

Turbulent mixing in pilot-scale cultivation systems influences the productivity of photoautotrophic cultures. We studied turbulent mixing by applying particle image velocimetry and acoustic doppler velocimetry to pilot-scale, flat-panel photobioreactor, and open-channel raceway. Mixing energy inputs were varied from 0.1 to 2.1 W·m-3 . The experimental results were used to quantify turbulence and to validate computational fluid dynamics models, from which Lagrangian representations of the fluid motion in these reactors were derived. The results of this investigation demonstrated that differences in mixing energy input do not significantly impact the structure of turbulence and the light/dark cycling frequencies experienced by photoautotrophic cells within the reactors. The experimental and computational results of our research demonstrated that well-mixed conditions exist in pilot-scale, flat-panel photobioreactors and open-channel raceways, even for relatively low mixing energy inputs.