An Argument for a Hybrid HTN/Operator-Based Approach to Planning
Work on generative planning systems has focused on two diverse approaches to plan construction.
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Work on generative planning systems has focused on two diverse approaches to plan construction.
Batteries keep devices working by utilizing high energy density, however, they can run down and take tens of minutes to hours to recharge. For rapid power delivery and recharging, high-power density devices, i.e., supercapacitors, are used. The electrochemical processes which occur in batteries and supercapacitors give rise to different charge-storage properties. In lithium ion (Li+) batteries, the insertion of Li+, which enables redox reactions in bulk electrode materials, is diffusion controlled and can be slow. Supercapacitor devices, also known as electrical double-layer capacitors (EDLCs) store charge by adsorption of electrolyte ions onto the surface of electrode materials. No redox reactions are necessary, so the response to changes in potential without diffusion limitations is rapid and leads to high power. However, the charge in EDLCs is confined to the surface, so the energy density is lower than that of batteries.
The cross-field current instability (CCI) was proposed elsewhere as a plausible mechanism for the initiation and intensification of substorm expansions. This instability encompasses the modified two stream, the ion-Weibel and the lower hybrid drift modes. The work carried out in relation to this instability and its local and global effects is reviewed. Predicted local effects include current reduction, particle acceleration, the excitation of oblique whistlers and lower hybrid drift waves, and the breakdown of the frozen-in-field condition through anomalous dissipation. The predicted global effects of CCI include the offset of force equilibrium and the generation of field aligned currents at the disruption site, which allow the efficient large scale transportation of mass, momentum and energy within the magnetosphere.
Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.
Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. One remaining issue is the cost of hybrids versus the existing launch propulsion systems. This paper will review the known state-of-the-art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.
The Human Integrated Vehicles and Environments (HIVE) lab at Johnson Space Center (JSC) is focused on bringing together inter-disciplinary talent to design and integrate innovative human interface technologies for next generation manned spacecraft. As part of this objective, my summer internship project centered on an ongoing investigation in to building flight displays using the HTML5 standard. Specifically, the goals of my project were to build and demo "flight-like" crew and wearable displays as well as create a webserver for live systems being developed by the Advanced Exploration Systems (AES) program. In parallel to my project, a LabVIEW application, called a display server, was created by the HIVE that uses an XTCE (XML (Extensible Markup Language) Telemetry and Command Exchange) parser and CCSDS (Consultative Committee for Space Data System) space packet decoder to translate telemetry items sent by the CFS (Core Flight Software) over User Datagram Protocol (UDP). It was the webserver's job to receive these UDP messages and send them to the displays. To accomplish this functionality, I utilized Node.js and the accompanying Express framework. On the display side, I was responsible for creating the power system (AMPS) displays. I did this by using HTML5, CSS and JavaScript to create web pages that could update and change dynamically based on the data they received from the webserver. At this point, I have not started on the commanding, being able to send back to the CFS, portion of the displays but hope to have this functionality working by the completion of my internship. I also created a way to test the webserver's functionality without the display server by making a JavaScript application that read in a comma-separate values (CSV) file and converted it to XML which was then sent over UDP. One of the major requirements of my project was to build everything using as little preexisting code as possible, which I accomplished by only using a handful of JavaScript libraries. As a side project, I created a model of the HIVE lab and Building 29 using SketchUp. I obtained the floorplans of the building from the JSC Geographic Information Systems (GIS), which were computer-aided design (CAD) files, and imported them into SketchUp. I then took those floorplans and created a 3D model of the building from them. Working in conjunction with the Hybrid Reality lab in Building 32, the SketchUp model was imported into Unreal Engine for use with the HTC Vive. Using the Vive, I was able to interact with the model I created in virtual reality (VR). The purpose of this side project was to be able to visualize potential lab layouts and mockup designs as they are in development in order to finalize design decisions. Pending approval, the model that I created will be used in the Build-As-You-Test: Can Hybrid Reality Improve the SE/HSI Design Process project in the fall. Getting the opportunity to work at NASA has been one of the most memorable experiences of my life. Over the course of my internship, I improved my programming and web development abilities substantially. I will take all the skills and experiences I have had while at NASA back to school with me in the fall and hope to pursue a career in the aerospace industry after graduating in the spring.
In this work, several mini-apps have been created to enhance a real-world application performance, namely the VULCAN code for complex flow analysis developed at the NASA Langley Research Center. These mini-apps explore hybrid parallel programming paradigms with Message Passing Interface (MPI) for distributed memory access and either Shared MPI (SMPI) or OpenMP for shared memory accesses. Performance testing shows that MPI+SMPI yields the best execution performance, while requiring the largest number of code changes. A maximum speedup of 23X was measured for MPI+SMPI, but only 10X was measured for MPI+OpenMP.
Previous work has demonstrated the large potential for hybrid active-passive systems for attenuating interior noise in aircraft fuselages. The main advantage of an active-passive system is, by utilizing the natural dynamics of the actuator system, the control actuator power and weight is markedly reduced and stability/robustness is enhanced. Three different active-passive approaches were studied in the past year. The first technique utilizes multiple tunable vibration absorbers (ATVA) for reducing narrow band sound radiated from panels and transmitted through fuselage structures. The focus is on reducing interior noise due to propeller or turbo fan harmonic excitation. Two types of tunable vibration absorbers were investigated; a solid state system based upon a piezoelectric mechanical exciter and an electromechanical system based upon a Motran shaker. Both of these systems utilize a mass-spring dynamic effect to maximize tile output force near resonance of the shaker system and so can also be used as vibration absorbers. The dynamic properties of the absorbers (i.e. resonance frequency) were modified using a feedback signal from an accelerometer mounted on the active mass, passed through a compensator and fed into the drive component of the shaker system (piezoelectric element or voice coil respectively). The feedback loop consisted of a two coefficient FIR filter, implemented on a DSP, where the input is acceleration of tile ATVA mass and the output is a force acting in parallel with the stiffness of the absorber. By separating the feedback signal into real and imaginary components, the effective natural frequency and damping of the ATVA can be altered independently. This approach gave control of the resonance frequencies while also allowing the simultaneous removal of damping from the ATVA, thus increasing the ease of controllability and effectiveness. In order to obtain a "tuned" vibration absorber the chosen resonant frequency was set to the excitation frequency. In order to minimize sound radiation a gradient descent algorithm was developed which globally adapted the resonance frequencies of multiple ATVA's while minimizing a cost based upon the radiated sound power or sound energy obtained from an array of microphones.
The CAWAPI-2 coordinated project has been underway to improve CFD predictions of slender airframe aerodynamics. The work is focused on two flow conditions and leverages a unique flight data set obtained with the F-16XL aircraft for comparison and verification. These conditions, a low-speed high angle-of-attack case and a transonic low angle-of-attack case, were selected from a prior prediction campaign wherein the CFD failed to provide acceptable results. In re-visiting these two cases, approaches for improved results include better, denser grids using more grid adaptation to local flow features as well as unsteady higher-fidelity physical modeling like hybrid RANS/URANS-LES methods. The work embodies predictions from multiple numerical formulations that are contributed from multiple organizations where some authors investigate other possible factors that could explain the discrepancies in agreement, e.g. effects due to deflected control surfaces during the flight tests, as well as static aeroelastic deflection of the outer wing. This paper presents the synthesis of all the results and findings and draws some conclusions that lead to an improved understanding of the underlying flow physics, and finally making the connections between the physics and aircraft features.
Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and later on solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. A remaining issue is the cost of hybrids vs the existing launch propulsion systems. This paper will review the known state of the art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.
How a neural network can work, compared to a hybrid system based on an operations research and artificial intelligence approach, is investigated through a mission scheduling problem. The characteristic features of each system are discussed.
An introduction to the major issues encountered in the readout of imaging detector arrays in the infrared are presented. These include circuit issues such as multiplexing, buffering, and noise, as well as materials issues. Future directions in infrared readout electronics will also be discussed. These include on-chip signal processing and advanced hybridization schemes. Finally, recent work at Columbia on 2DEG-charge coupled devices for IR detector multiplexing are described.
Recognition of partially occluded objects has been an important issue to airport security because occlusion causes significant problems in identifying and locating objects during baggage inspection. The neural network approach is suitable for the problems in the sense that the inherent parallelism of neural networks pursues many hypotheses in parallel resulting in high computation rates. Moreover, they provide a greater degree of robustness or fault tolerance than conventional computers. The annealed Hopfield network which is derived from the mean field annealing (MFA) has been developed to find global solutions of a nonlinear system. In the study, it has been proven that the system temperature of MFA is equivalent to the gain of the sigmoid function of a Hopfield network. In our early work, we developed the hybrid Hopfield network (HHN) for fast and reliable matching. However, HHN doesn't guarantee global solutions and yields false matching under heavily occluded conditions because HHN is dependent on initial states by its nature. In this paper, we present the annealed Hopfield network (AHN) for occluded object matching problems. In AHN, the mean field theory is applied to the hybird Hopfield network in order to improve computational complexity of the annealed Hopfield network and provide reliable matching under heavily occluded conditions. AHN is slower than HHN. However, AHN provides near global solutions without initial restrictions and provides less false matching than HHN. In conclusion, a new algorithm based upon a neural network approach was developed to demonstrate the feasibility of the automated inspection of threat objects from x-ray images. The robustness of the algorithm is proved by identifying occluded target objects with large tolerance of their features.
The present work involves generation of hybrid prismatic/tetrahedral grids for complex 3-D geometries including multi-body domains. The prisms cover the region close to each body's surface, while tetrahedra are created elsewhere. Two developments are presented for hybrid grid generation around complex 3-D geometries. The first is a new octree/advancing front type of method for generation of the tetrahedra of the hybrid mesh. The main feature of the present advancing front tetrahedra generator that is different from previous such methods is that it does not require the creation of a background mesh by the user for the determination of the grid-spacing and stretching parameters. These are determined via an automatically generated octree. The second development is a method for treating the narrow gaps in between different bodies in a multiply-connected domain. This method is applied to a two-element wing case. A High Speed Civil Transport (HSCT) type of aircraft geometry is considered. The generated hybrid grid required only 170 K tetrahedra instead of an estimated two million had a tetrahedral mesh been used in the prisms region as well. A solution adaptive scheme for viscous computations on hybrid grids is also presented. A hybrid grid adaptation scheme that employs both h-refinement and redistribution strategies is developed to provide optimum meshes for viscous flow computations. Grid refinement is a dual adaptation scheme that couples 3-D, isotropic division of tetrahedra and 2-D, directional division of prisms.
Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies (PISCES) is a prototype lenslet array based integral field spectrometer (IFS) designed for high contrast imaging of extrasolar planets. PISCES will be used to advance the technology readiness of the high contrast IFS baselined on the Wide-Field InfraRed Survey TelescopeAstrophysics Focused Telescope Assets (WFIRSTAFTA) coronagraph instrument. PISCES will be integrated into the high contrast imaging testbed (HCIT) at the Jet Propulsion Laboratory and will work with both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC). We will present the PISCES optical design, including the similarities and differences of lenslet based IFSs to normal spectrometers, the trade-off between a refractive design and reflective design, as well as the compatibility to upgrade from the current 1k x 1k detector array to 4k x 4k detector array. The optical analysis, alignment plan, and mechanical design of the instrument will be discussed.
Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies (PISCES) is a lenslet array based integral field spectrometer (IFS) designed for high contrast imaging of extrasolar planets. PISCES will be used to advance the technology readiness of the high contrast IFS baselined on the Wide-Field InfraRed Survey Telescope/Astrophysics Focused Telescope Assets (WFIRST/AFTA) coronagraph instrument. PISCES will be integrated into the high contrast imaging testbed (HCIT) at the Jet Propulsion Laboratory and will work with both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC) cofigurations. We discuss why the lenslet array based IFS is selected for PISCES. We present the PISCES optical design, including the similarities and differences of lenslet based IFSs to normal spectrometers, the trade-off between a refractive design and reflective design, as well as the specific function of our pinhole mask on the back surface of the lenslet array to further suppress star light introduced speckles. The optical analysis, alignment plan, and mechanical design of the instrument will be discussed.
Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies (PISCES) is a lenslet array based integral field spectrometer (IFS) designed for high contrast imaging of extrasolar planets. PISCES will be used to advance the technology readiness of the high contrast IFS baselined on the Wide-Field InfraRed Survey Telescope/Astrophysics Focused Telescope Assets (WFIRST-AFTA) coronagraph instrument. PISCES will be integrated into the high contrast imaging testbed (HCIT) at the Jet Propulsion Laboratory (JPL) and will work with both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC) configurations. We discuss why the lenslet array based IFS was selected for PISCES. We present the PISCES optical design, including the similarities and differences of lenslet based IFSs to normal spectrometers, the trade-off between a refractive design and reflective design, as well as the specific function of our pinhole mask on the back surface of the lenslet array to reduce the diffraction from the edge of the lenslets. The optical analysis, alignment plan, and mechanical design of the instrument will be discussed.
GMAO has developed a highly sophisticated adjoint modeling system based on the most recent version of the finite volume cubed sphere (FV3) dynamical core. This provides a mechanism for investigating sensitivity to initial conditions and examining observation impacts. It also allows for the computation of singular vectors and for the implementation of hybrid 4DVAR. In this work we will present the scientific assessment of the new adjoint system and show results from a number of research application of the adjoint system.