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The efficiency in energy consumption of an electric vehicle (EV) has significant value to both vehicle manufacturers and vehicle owners. Such efficiency will directly impact the cost of energy and vehicle range while relieving the stringent requirements on the DC motor and battery specs. Nowadays, with the development of advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC) or cooperative adaptive cruise control (CACC), drivers enjoy a much safer driving experience. ADAS capabilities in sensory, computing and communication can be leveraged in EVs for the purpose of optimizing energy consumption. This paper introduces an energy-optimized ACC platform, which utilizes a forecast of the speed profile of the host vehicle in a short (few seconds) horizon. Such speed information can be available through ADAS or similar systems. This paper focuses on optimization in longitudinal tracks.

The blend of dimethyl ether (DME, CH3OCH3) and propane (C3H8) is a potentially renewable fuel mixture that has the potential to replace diesel in compression ignition engines. The combination can potentially reduce particulate and greenhouse gas emissions compared to a conventional diesel engine operating under similar conditions. However, detailed conceptual and simulation studies must be conducted before adopting a new fuel on a compression ignition engine. For these simulations, accurate chemical kinetic models are necessary. However, the validity of chemical kinetic mechanisms in the literature is unknown for mixing controlled compression ignition (MCCI) engine operating conditions. Hence, in this work, we studied the ignition of dimethyl ether (DME) and propane blends in a shock tube at MCCI engine conditions. Ignition delay time (IDT) data was collected behind the reflected shock for DME-propane mixtures for heavy-duty compression ignition (CI) engine parameters.

The making of a quilt is an interesting process. Historically, a quilt is a canvas of work made from old pieces of cloth cut into squares or whatever shape that make a nice connected pattern and then stitched together. The quilt could be random pieces that is not related to each other. In most recent years and more common cases, a quilt is made of different pieces of patches that are connected and laid out in a special way to tell a story. Not only does it portray a story that is put together in a certain sequence, but it also stiches the pieces of the quilt into a nice and complete narrative. A story that one can understand just by looking at the quilt spread and unfolded. Much like the making of a quilt that has a story to tell, a Product Digital Quilt will tell the story of a product. The Digital Product Quilt replaces the conventional way of telling a product story. The traditional product story is a method that is serially connecting multiple product life cycle silos together.

Connected and Autonomous Vehicles (CAV) rely on information obtained from sensors and communication to make decisions. In a Cooperative Vehicle Safety (CVS) system, information from remote vehicles (RV) is available at the host vehicle (HV) through the wireless network. Safety applications such as crash warning algorithms use this information to estimate the RV and HV states. However, this information is uncertain and sparse due to communication losses, limitations of communication protocols in high congestion scenarios, and perception errors caused by sensor limitations. In this paper we present a novel approach to improve the robustness of the CVS systems, by proposing an architecture that divide application and information/perception subsystems and a novel prediction method based on non-parametric Bayesian inference to mitigate the detrimental effect of data loss on the performance of safety applications.

Co-Optimization of Fuels and Engines initiative (Co-Optima) of the U.S Department of Energy started investigations on several candidates of biofuels and blends for internal combustion engines. At this stage, only a few biomass-derived fuel blendstocks (including ethanol) for advanced spark-ignition engines have been selected using enhanced screening criteria, which included boiling point, toxicity, research octane number, octane sensitivity, and economical distribution system, etc. Ethanol, of which this paper is focused on, is also an important fuel because of its high-octane number which in turn promotes advance ignition timing and higher thermal efficiencies in reciprocating engines. Measurements of laminar burning velocity (LBV) is a key metric to understand fuel performance and applicability in engines. Furthermore, in order to quantify more complicated, and practical, burning regimes such as turbulent combustion much of the underlying theory requires knowledge of LBV.

The battery is a central part of the vehicle’s electrical system and has to undergo cycling in a wide variety of conditions while providing an acceptable service life. Within a typical distribution chain, automotive lead-acid batteries can sit in storage for months before delivery to the consumer. During storage, batteries are subjected to a wide variety of temperature profiles depending on facility-specific characteristics. Additionally, batteries typically do not receive any type of maintenance charge before delivery. Effects of storage time, temperature, and maintenance charging are explored. Flooded lead-acid batteries were examined immediately after storage and after installation in vehicles subjected to normal drive patterns. While phase composition is a major consideration, additional differences in positive active material (PAM) were observed with respect to storage parameters.

Laminar burning velocity (LBV) measurements are reported for promising high-performance fuels selected as drop-in transportation fuels to automotive grade gasoline as part of the United States Department of Energy’s Co-Optimization of Fuels and Engines Initiative (Co-Optima). LBV measurements were conducted for ethanol, methyl acetate, and 2-methylfuran with synthetic air (79.0 % N2 and 21.0 % O2 by volume) within a constant-volume spherical combustion rig. Mixture initial temperature was fixed at 428±4 K, with the corresponding initial pressure of 1.00±0.02 atm. Current LBV of ethanol is in good agreement with literature data. LBV of ethanol and 2-methylfuran showed similar values over the range of equivalence ratios, while methyl acetate exhibited an LBV significantly lower over the range of tested equivalence ratios. The maximum laminar burning velocity occurred at slightly richer equivalence ratio from the stoichiometric value for all fuels tested.

Aerospace projects live a long time. Around the turn of the century, NASA first began to discuss multi-decadal projects with respect to the tools, methods, infrastructure and culture necessary to successfully establish outposts and bases both on the Moon as well as in adjacent space. Pilot projects were completed, capabilities developed and solutions were shared across the Agency. A decade later the Mars discussion was multi-generational with planning milestones 50 years in the future. The 1970’s Requirements Document, or the 1990’s System Model are nowhere near suitable for planning, development, integration and operations of multi-national, highly complex, incredibly expensive development efforts planned to outlast not only the careers of the developers but that of their children as well. Simulation in the different forms has become very important for this multi-decadal projects. The challenge will be to device ways to create formats and views which can stand time.

The Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M&S) of many techniques are used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most of WCE research using the Defense Modeling and Simulation (DM&S) techniques studied have considered a lot of assumptions and limited scenarios without the help of big data technologies. Furthermore, WCE analytics using previous methodologies cannot help but get the bias results. This paper reviews and combines the basic knowledge for the new WCE analytics methodology using big data and M&S to overcome these problems of bias. Then this paper reviews the general overview of WCE, DM&S, and big data.

In this study we consider the coordinated exploration of an unfamiliar Martian landscape by a swarm of small autonomous rovers, called Swarmies, simulated in a distributed setting. With a sustainable program of return missions to and from Mars in mind, the goal of said exploration is to efficiently prospect the terrain for water meant to be gathered and then utilized in the production of rocket fuel. The rovers are tasked with relaying relevant data to a home base that is responsible for maintaining a mining schedule for an arbitrarily large group of rovers extracting water-rich regolith. For this reason, it is crucial that the participants maintain a wireless connection with one another and with the base throughout the entire process. We describe the architecture of our simulation which is composed of HLA-compliant components that are visualized via the Distributed Observer Network tool developed by NASA.

Multi-Resolution Modeling (MRM) is one of the key technologies for building complex and large-scale simulations using legacy simulators. MRM has been developed continuously, especially in military fields. MRM plays a crucial role to describe the battlefield and gathering the desired information efficiently by linking various levels of resolution. The simulation models interact across different local and/or distance area networks using the High Level Architecture (HLA) regardless of their operating systems and hardware. The HLA is a standard architecture developed by the US Department of Defense (DoD) and is meant to create interoperability among different types of simulators. Therefore, MRM implementations are very dependent on Interoperability and Composability. This paper summarizes the definition of MRM-related terminology and proposes a basic form of MRM system using Commercial Off-The-Shelf (COTS) simulators and HLA.

The 2,4-dimethyl-3-pentanone (DIPK) is a promising biofuel candidate for automotive applications that is produced by the endophytic fungal conversion process which can be optimized for widespread utilization. There are some studies in the literature on combustion properties of DIPK, such as ignition delay times and laminar burning velocity (LBV) measurements. However, most studies are conducted one atmospheric (atm) pressure which are far away from the high-pressure conditions present inside reciprocating engines. Therefore, we present LBV measurements at high pressures up to 10 atm for this fuel using a spherical flame speed facility. It is known that the flame in a constant volume chamber develops cellular structure (hydrodynamic instability) as the initial pressure increases because of the reduction in flame thickness. In addition, the diffusional-thermal instability prevents experiments for rich mixtures because of the reduction of Lewis number (Le).

Operator training using a weapon in a real-world environment is risky, expensive, time-consuming, and restricted to the given environment. In addition, governments are under intense scrutiny to provide security, yet they must also strive for efficiency and reduce spending. In other words, they must do more with less. Virtual simulation, is usually employed to solve these limitations. As the operator is trained to maximize weapon effectiveness, the effectiveness-focused training can be completed in an economical manner. Unfortunately, the training is completed in limited scenarios without objective levels of training factors for an individual operator to optimize the weapon effectiveness. Thus, the training will not be effective. For overcoming this problem, we suggest a methodology on guiding effectiveness-focused training of the weapon operator through usability assessments, big data, and Virtual and Constructive (VC) simulations.

The future of human exploration in the solar system is contingent on the ability to exploit resources in-situ to produce mission consumables. Specifically, it has become clear that the success of a manned mission to Mars will likely depend on fuel components created on the Martian surface. While several architectures for an unmanned fuel production surface facility on Mars exist in theory, a simulation of the performance and operation of these architectures has not been created. In this paper, the framework describing a simulation of one such architecture is defined. Within this architecture, each component of the base is implemented as a state machine, with the ability to communicate with other base elements as well as a supervisor. An environment supervisor is also created which governs low level aspects of the simulation such as movement and resource distribution, in addition to higher-level aspects such as location selection with respect to operations specific behavior.

The biofuel and engine co-development framework was initiated at Sandia National Labs. Here, the synthetic biologists develop and engineer a new platform for drop-in fuel production from lignocellulosic biomass, using several endophytic fungi. Hence this process has the potential advantage that expensive pretreatment and fuel refining stages can be optimized thereby allowing scalability and cost reduction; two major considerations for widespread biofuel utilization. Large concentrations of ketones along with other volatile organic compounds were produced by fungi grown over switchgrass media. The combustion and emission properties of these new large ketones are poorly known.

For aircraft electromechanical actuator (EMA) cooling applications using forced air produced by axial fans, the main objective in fan design is to generate high static pressure head, high volumetric flow rate, and high efficiency over a wide operating range of rotational speed (1x∼3x) and ambient pressure (0.2∼1 atm). In this paper, a fan design based on a fan diameter of 86 mm, fan depth (thickness) of 25.4 mm, and hub diameter of 48 mm is presented. The blade setting angle and the chord lengths at the leading and trailing edges are varied in their suitable ranges to determine the optimal blade profiles. The fan static pressure head, volumetric flow rate, and flow velocity are calculated at various ambient pressures and rotational speeds. The optimal blade design in terms of maximum total-to-total pressure ratio and efficiency at the design point is obtained via CFD simulation. A 5-blade configuration yields the best performance in terms of efficiency and total pressure ratio.

The aircraft electromechanical actuator (EMA) cooling fan is a critical component because an EMA failure caused by overheating could lead to a catastrophic failure in aircraft. Fault tree analysis (FTA) is used to access the failure probability of EMA fans with the goal of improving their mean time to failure (MTTF) from ∼O(5×104) to ∼ O(2.5×109) hours without incurring heavy weight penalty and high cost. The dual-winding and dual-bearing approaches are analyzed and a contra rotating dual-fan design is proposed. Fan motors are assumed to be brushless direct current (BLDC) motors. To have a full understanding of fan reliability, all possible failure mechanisms and failure modes are taken into account. After summarizing the possible failure causes and failure modes of BLDC fans by focusing on each failure mechanism, the life expectancy of fan ball bearings based on a major failure mechanism of lubricant deterioration is calculated and compared to that provided in the literature.

In this paper, we address the thermal management issues which limit the lifespan, specific power and overall efficiency of an air-cooled rotary Wankel engine used in Unmanned Air Vehicles (UAVs). Our goal is to eliminate the hot spots and reduce the temperature gradients in the engine housing and side plates by aggressive heat spreading using heat pipes. We demonstrate by simulation that, for a specific power requirement, with heat spreading and more effective heat dissipation, thermal stress and distortion can be significantly reduced, even with air cooling. The maximum temperature drop was substantial, from 231°C to 129°C. The temperature difference (measure of temperature uniformity) decreased by 8.8 times (from 159°C to 18°C) for a typical UAV engine. Our heat spreaders would not change the frontal area of the engine and should have a negligible impact on the installed weight of the propulsion assembly.

The scaling laws of fans express basic relationships among the variables of fan static pressure head, volume flow rate, air density, rotational speed, fan diameter, and power. These relationships make it possible to compare the performance of geometrically similar fans in dissimilar conditions. The fan laws were derived from dimensionless analysis of the equations for volumetric flow rate, static pressure head, and power as a function of fan diameter, air density and rotational speed. The purpose of this study is to characterize a fan's performance characteristics at various rotational speeds and ambient pressures. The experimental results are compared to the fan scaling laws.

The term “productivity” all too often has becomes a buzz-word, ultimately diminishing its perceived importance. However, productivity is the major concern of any team, and therefore must be defined to gain an appropriate understanding of how a system is actually working. Here, productivity means the level of contribution to the throughput of a system such as defined in the Theory of Constraints. In the field of space exploration, the throughput is the number of milestones of the mission accomplished as well as the potential survival during extreme events (due to failures or other unplanned events). For a time tasks were accomplished by expert individuals (e.g., an astronaut), but recently team structures have become the norm. It is clear that with increased mission complexity, “no single entity can have complete knowledge of or the abilities to handle all matters” [10].