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MIL-STD-704 defines power quality in terms of transient, steady-state, and frequency-domain metrics that are applicable throughout a military aircraft electric power system. Maintaining power quality in more electric aircraft power systems has become more challenging in recent years due to the increase in load dynamics and power levels in addition to stricter requirements of power system characteristics during a variety of operating conditions. Further, power quality is often difficult to assess directly during experiments and aircraft operation or during data post-processing for the integrated electric power system (including sources, distribution, and loads). While MIL-STD-704 provides guidelines for compliance testing of electric load equipment, it does not provide any instruction on how to assess the power quality of power sources or the integrated power system itself, except the fact that power quality must be satisfied throughout all considered operating conditions.

Experimental Hardware-in-the-loop (xHIL) testing utilizing signal and/or power emulation imposes a hard real-time requirement on models of emulated subsystems, directly limiting their fidelity to what can be achieved in real-time on the available computational resources. Most real-time simulators are CPU-based, for which the overhead of an instruction-set architecture imposes a lower limit on the simulation step size, resulting in limited model bandwidth. For power-electronic systems with high-frequency switching, this limit often necessitates using average-value models, significantly reducing fidelity, in order to meet the real-time requirement. An alternative approach emerging recently is to use FPGAs as the computational platform, which, although offering orders-of-magnitudes faster execution due to their parallel architecture, they are more difficult to program and their limited fabric space bounds the size of models that can be simulated.

This paper introduces a method for conducting experimental hardware-in-the-loop (xHIL), in which behavioral-level models are coupled with an advanced power emulator (APE) to emulate an electrical load on a power generation system. The emulator is commanded by behavioral-level models running on an advanced real-time simulator that has the capability to leverage Central Processing Units (CPUs) and field programmable gate arrays (FPGA) to meet strict real-time execution requirements. The paper will be broken down into four topics: 1) the development of a solution to target behavioral-level models to an advanced, real-time simulation device, 2) the development of a high-bandwidth, high-power emulation capability, 3) the integration of the real-time simulation device and the APE, and 4) the application of the emulation system (simulator and emulator) in an xHIL experiment.

Movement toward more-electric architectures in military and commercial airborne systems has led to electrical power systems (EPSs) with complex power flow dynamics and advanced technologies specifically designed to improve power quality in the system. As such, there is a need for tools that can quickly analyze the impact of technology insertion on the system-level dynamic transient and spectral power quality and assess tradeoffs between impact on power quality versus weight and volume. Traditionally, this type of system level analysis is performed through computationally intensive time-domain simulations involving high fidelity models or left until the hardware fabrication and integration stage. In order to provide a more rapid analysis prior to hardware development and integration, stochastic equivalent circuit analysis is developed that can provide power quality assessment directly in the frequency domain.

Deep-hole drilling is among the most critical precision machining processes for production of high-performance discrete components. The effects of drilling with superimposed, controlled low-frequency modulation - Modulation-Assisted Machining (MAM) - on the surface textures created in deep-hole drilling (ie, gun-drilling) are discussed. In MAM, the oscillation of the drill tool creates unique surface textures by altering the burnishing action typical in conventional drilling. The effects of modulation frequency and amplitude are investigated using a modulation device for single-flute gun-drilling on a computer-controlled lathe. The experimental results for the gun-drilling of titanium alloy with modulation are compared and contrasted with conventional gun-drilling. The chip morphology and surface textures are characterized over a range of modulation conditions, and a model for predicting the surface texture is presented. Implications for production gun-drilling are discussed.

The diverse and complex requirements of next-generation energy optimized aircraft (EOA) demand detailed transient and dynamic model-based design (MBD) to ensure the proper operation of numerous interconnected and interacting subsystems. In support of the U.S. Air Force's Integrated Vehicle Energy Technology (INVENT) program, several software tools have been developed and are in use that aid in the efficient MBD of next-generation EOA. Among these are subsystem model libraries, automated subsystem model verification test scripts, a distributed co-simulation application, and tools for system configuration, EOA mission building, data logging, plotting, post-processing, and visualization, and energy flow analysis. Herein, each of these tools is described. A detailed discussion of each tool's functionality and its benefits with respect to the goal of achieving successful integrated system simulations in support of MBD of EOA is given.

Minimizing energy use on more electric aircraft (MEA) requires examining in detail the important decision of whether and when to use engine bleed air, ram air, electric, hydraulic, or other sources of power. Further, due to the large variance in mission segments, it is unlikely that a single energy source is the most efficient over an entire mission. Thus, hybrid combinations of sources must be considered. An important system in an advanced MEA is the adaptive power and thermal management system (APTMS), which is designed to provide main engine start, auxiliary and emergency power, and vehicle thermal management including environmental cooling. Additionally, peak and regenerative power management capabilities can be achieved with appropriate control. The APTMS is intended to be adaptive, adjusting its operation in order to serve its function in the most efficient and least costly way to the aircraft as a whole.

A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

A layered approach to the simulation of dynamically interdependent systems is presented. In particular, the approach is applied to the integrated engineering plant of a notional all-electric warship. The models and parameters of the notional ship are presented herein. This approach is used to study disruptions to the integrated engineering plant caused by anti-ship missiles. Example simulation results establish the effectiveness of this approach in examining the propagation of faults and cascading failures throughout a dynamically interdependent system of systems.

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.

In long-duration, closed human habitats in space that include crop growth, one challenge that is faced while designing a candidate waste processor is the composition of solid-waste loads, which include human waste, packaging and food-processing materials, crop spoilage, and plant residues. In this work, a new modeling tool is developed to characterize crop residues and food wastes based on diet in order to support the design of solid-waste technologies for closed systems. The model predicts amounts of crop residues and food wastes due to food processing, crop harvests, and edible spoilage. To support the design of solid-waste technologies, the generation of crop residues and food wastes was characterized for a 600-day mission to Mars using integrated menu, crop, and waste models. The three sources of plant residues and food waste are identified to be food processors, crop harvests, and edible spoilage.

The new devices and missions to achieve the aims of NASA's Science Mission Directorate (SMD) are creating increasingly demanding thermal environments and applications. In particular, the low conductance of metal-to-metal interfaces used in the thermal switches lengthen the cool-down phase and resource usage for spacecraft instruments. During this work, we developed and tested a vacuum-compatible, durable, heat-conduction interface that employs carbon nanotube (CNT) arrays directly anchored on the mating metal surfaces via microwave plasma-enhanced, chemical vapor deposition (PECVD). We demonstrated that CNT-based thermal interface materials have the potential to exceed the performance of currently available options for thermal switches and other applications.

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.

Dynamics of machine tool components play a critical role in the outcome of machining processes. This paper addresses several important issues on machine tool and machining dynamics. It illustrates the dynamic behavior of structural components under operating conditions and presents an improved technique for modeling structural non-linearity. It also describes spindle modeling capability that has been developed to predict dynamic and thermal characteristics of spindle systems. Finally, the paper discusses the impact of non-linear dynamics on machining stability.

This paper presents in-process monitoring and control based on a novel ultrasonic sensing technique. The developed ultrasonic system provides non-contact measurement of surface roughness, which is applicable to wet machining environments. The utility and robustness of the technique are demonstrated through applications to different processes and materials. In-process surface roughness monitoring capability of the system is also shown along with its potential to monitor flank wear conditions. The result of in-process surface roughness control implementation based on the developed technique shows the control scheme is able to maintain consistent surface roughness values regardless of the tool wear state.

Detailed computer models of system components for More Electric Aircraft have been developed using the Advanced Control System Language (ACSL) and its graphical front-end, Graphic Modeller. Among the devices modeled are a wound-rotor synchronous generator with parallel bridge-rectifier outputs, a switched-reluctance generator, and various loads including a DC-DC converter, an inverter-driven induction motor, and an electro-hydrostatic actuator. Results from the simulations are presented together with corroborating experimental test results.

In this paper, a recently-developed algorithmic method of deriving the state equations of power systems containing power electronic components is described. Therein the system is described by the pertinent branch parameters and the circuit topology; however, unlike circuit-based algorithms, the difference equations are not implemented at the branch level. Instead, the composite system state equations are established. A demonstration of the computer implementation of this algorithm to model a variable-speed, constant-frequency aircraft generation system is described. Because of the large number of states and complexity of the system, particular attention is placed on the development of a model structure which provides optimal simulation efficiency.

The method of multiple reference frames is employed in the development of a state variable model for brushless DC drives with non-sinusoidal back emf waveforms. This model has the desirable features of being valid for transient and steady-state analysis as well as having state variables that are constant in the steady-state. The model facilitates both nonlinear and linear system analysis and control design. Computer simulation and experimental data are included to validate the analysis.

The negative consequences of unsafe behaviors on the job heavily contribute to the rising costs of doing business in terms of both organization dollars and diminished human quality of life. Developing a safety culture provides a positive proactive approach toward creating a working environment where safety is a top priority. An integral part of accomplishing this task is directly related to training individuals on how the interactions that occur among organizational members and the messages their behaviors send influence others' behaviors. This can be best addressed through communication skill development initiatives including mutual responsibility, trust, avoiding punitive strategies and facilitating assertiveness.

This paper introduces an integration-level analysis tool to provide feedback for high-level trade spaces. The Purdue University Lunar C3I Model integrates approximations of several domain-specific models to simulate for many years the effect of network and asset parameters. This paper discusses the communication, anomaly response, and autonomy simulation models in depth. Results of these models provide specific examples of integration-level figures of merit that can be useful for comparing different campaign implementations. These figures of merit are contrasted with related domain-specific figures of merit in order to demonstrate the need for higher-level system integration decisions. A final example of integration-level results and interpretation discusses the autonomy level of the Altair lunar lander.