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At least 145 records · Page 8

Programmable Oscillator

A programmable oscillator is a frequency synthesizer with an output phase that tracks an arbitrary function. An offset, phase-locked loop circuit is used in combination with an error control feedback loop to precisely control the output phase of the oscillator. To down-convert the received signal, several stages of mixing may be employed with the compensation for the time-base distortion of the carrier occurring at any one of those stages. In the Goldstone Solar System Radar (GSSR), the compensation occurs in the mixing from an intermediate frequency (IF), whose value is dependent on the station and band, to a common IF used in the final stage of down-conversion to baseband. The programmable oscillator (PO) is used in the final stage of down-conversion to generate the IF, along with a time-varying phase component that matches the time-base distortion of the carrier, thus removing it from the final down-converted signal.

Quirk, Kevin J.↗

Programmable Ultra-Lightweight System Adaptable Radio

The programmable ultra-lightweight system adaptable radio (PULSAR) is a NASA Marshall Space Flight Center transceiver designed for the CubeSat market, but has the potential for other markets. The PULSAR project aims to reduce size, weight, and power while increasing telemetry data rate. The current version of the PULSAR has a mass of 2.2 kg and a footprint of 10.8 cm2. The height depends on the specific configuration. The PULSAR S-Band Communications Subsystem is an S- and X-band transponder system comprised of a receiver/detector (receiver) element, a transmitter element(s), and related power distribution, command, control, and telemetry element for operation and information interfaces. It is capable of receiving commands, encoding and transmitting telemetry, as well as providing tracking data in a manner compatible with Earthbased ground stations, near Earth network, and deep space network station resources. The software-defined radio's (SDR's) data format characteristics can be defined and reconfigured during spaceflight or prior to launch. The PULSAR team continues to evolve the SDR to improve the performance and form factor to meet the requirements that the CubeSat market space requires. One of the unique features is that the actual radio design can change (somewhat), but not require any hardware modifications due to the use of field programmable gate arrays.

Werkheiser, Arthur↗

The XXL Survey I. Scientific Motivations - Xmm-Newton Observing Plan - Follow-up Observations and Simulation Programme

The quest for the cosmological parameters that describe our universe continues to motivate the scientific community to undertake very large survey initiatives across the electromagnetic spectrum. Over the past two decades, the Chandra and XMM-Newton observatories have supported numerous studies of X-ray-selected clusters of galaxies, active galactic nuclei (AGNs), and the X-ray background. The present paper is the first in a series reporting results of the XXL-XMM survey; it comes at a time when the Planck mission results are being finalized. Aims. We present the XXL Survey, the largest XMM programme totaling some 6.9 Ms to date and involving an international consortium of roughly 100 members. The XXL Survey covers two extragalactic areas of 25 deg2 each at a point-source sensitivity of approx. 5 x 10(exp 15) erg/s/sq cm in the [0.5-2] keV band (completeness limit). The surveys main goals are to provide constraints on the dark energy equation of state from the space-time-distribution of clusters of galaxies and to serve as a pathfinder for future, wide-area X-ray missions. We review science objectives, including cluster studies, AGN evolution, and large-scale structure, that are being conducted with the support of approximately 30 follow-up programs. Methods. We describe the 542 XMM observations along with the associated multi- and numerical simulation programmes. We give a detailed account of the X-ray processing steps and describe innovative tools being developed for the cosmological analysis. Results. The paper provides a thorough evaluation of the X-ray data, including quality controls, photon statistics, exposure and background maps, and sky coverage. Source catalogue construction and multi-associations are briefly described. This material will be the basis for the calculation of the cluster and AGN selection functions, critical elements of the cosmological and science analyses. Conclusions. The XXL multi- data set will have a unique lasting legacy value for cosmological and extragalactic studies and will serve asa calibration resource for future dark energy studies with clusters and other X-ray selected sources. With the present article, we release the XMM XXL photon and smoothed images along with the corresponding exposure maps.

X-rays: general – large-scale structure of Unive↗

Field Programmable Gate Array Data Capture for Control Systems

Some Industrial Control Systems (ICS) networks are based on protocols such as Serial and Industrial Ethernet. These protocols currently have no existing cybersecurity monitoring tools, leaving a large gap in the cyber defense of critical infrastructure. In order to analyze such ICS traffic, it is first necessary to implement methods of capturing the ICS data. Whereas traditional methods of analyzing data would use microprocessors, the nature of high-speed analog data can be difficult to implement on such a versatile processor, as they are rather inefficient for doing a single task. Whereas Field Programmable Gate Arrays (FPGAs) provide an adequate tool in analyzing high speed data, as despite the lack of program versatility, Programmable Logic can implement a solution with minimal clock cycles, allowing time for each new packet of data to be captured before a new data sample is taken.

42 ENGINEERING↗

Embedded 3D printing of isotropically enhanced lattice structure with programmable elasticity via three-dimensional fiber alignment

Engineered composites with fiber orientation in a complete three-dimensional (3D) context are highly desired for maximizing structural performance as they mimic the well-organized fiber arrangement in natural composites. However, most fabrication techniques lack the capability for through-plane (z-axis) alignment, limiting the possibility for structural design and performance optimization. In this study, we present an embedded 3D printing approach that enables complete 3D fiber alignment, including region-specific alignment control along the through-plane direction. Our method utilizes the extrusion and suspension of composite inks within a supporting matrix. By regionally adjusting the ink extrusion rate and nozzle translation rate, we locally manipulated the fiber arrangement within the composite 3D architecture. Here, we demonstrate that the 3D alignment of carbon fibers in a structural composite significantly enhances both mechanical properties and thermal conductivity in the in-plane and through-plane directions. Furthermore, by strategically arranging regional fiber orientations within micro-architected materials, we fabricated metamaterial engineered composites with programmable anisotropy ratio and directional moduli.

36 MATERIALS SCIENCE↗

Detecting control system misbehavior by fingerprinting programmable logic controller functionality

In recent years, attacks such as the Stuxnet malware have demonstrated that cyberattacks against control systems cause extensive damage. These attacks can result in physical damage to the networked systems under their control. In this paper, we discuss our approach for detecting such attacks by distinguishing between programs running on a programmable logic controller (PLC) without having to monitor communications. Using power signatures generated by an attached, high-frequency power measurement device, we can identify what a PLC is doing and when an attack may have altered what the PLC should be doing. To accomplish this, we generated labeled data for testing our methods and applied feature engineering techniques and machine learning models. The results of this research demonstrate that Random Forests and Convolutional Neural Networks classify programs with up to 98% accuracy for major program differences and 84% accuracy for minor differences. Our results can be used for both online and offline applications.

97 MATHEMATICS AND COMPUTING↗

Catalytic resonance theory: Circumfluence of programmable catalytic loops

Chemical reactions on heterogeneous catalyst surfaces exhibit complex networks of elementary reactions with multiple pathways to fluid phase products, sometimes leading to surface reaction loops consisting of a closed cycle reaction pathway. While conventional catalysts at steady state exhibit zero net flux in either direction around a catalytic loop, the loop turnover frequency of three-species surface loops was evaluated in this work via microkinetic modeling to assess the reaction loop behavior resulting from a catalytic surface oscillating between two or more surface energy states. For dynamic heterogeneous catalysts undergoing applied oscillations of surface energy (i.e., programs), surface reaction loops of three species were shown to exhibit non-zero net flow of molecules around the loop, with the extent of loop turnover frequency varying with the applied frequency and amplitude of a sinusoidal or square wave oscillation. Alternatively, some dynamic surface reactions exhibited oscillations only between two surface species or resulted in surfaces covered by a single species at all times. Here, more complex behavior was observed for dynamic surface programs of three distinct electronic states, with the temporal order of applied states controlling the direction of flow of molecules within a three-molecule surface loop. Catalytic loops have the potential to limit overall catalytic reaction rates and use energy in programmable catalysts, while some applications could purposely impose non-zero loop turnover frequency for improved surface reaction control.

Catalysis↗

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Programmable Ultralight Magnets via Orientational Arrangement of Ferromagnetic Nanoparticles within Aerogel Hosts

The actuation and levitation of air-suspended objects by a magnetic field, due to its noncontact and holonomic manipulation modes, are important technological capabilities for device applications. However, owing to a higher density of conventional ferromagnets or nanoparticle-containing polymers and strong magnetic fields required for actuation, fabricating lightweight materials with a sensitive magnetic response for weight critical applications is challenging. Here, we report ultralight aerogel-based magnets (aero-magnets) comprising assembled ferromagnetic nanomaterials with highly magnetic anisotropy where the magnetic domains can be programmed by external predesigned fields. To demonstrate the breadth of manufacturing methods for this breed of aero-magnet composites, both silica/nanocellulose aerogel hosts and ferromagnetic nanorod/nanoplatelet guests have been explored. Single and double domains with out-of-plane magnetization are programmed into the aero-magnets and characterized by magnetic force microscopy. The levitation and actuation of the aero-magnets are realized while exposed to a small external magnetic field of 11 mT and introduced to a switching circuit. Furthermore, the elastic moduli of the aero-magnets are estimated by dynamic magnetic responses of the ferromagnetic nanoparticles tightly tethered in the aerogel hosts under rapid cyclic fields. These programmable aero-magnets could serve as monolithic magnetic actuator units in the fields of tiny robots and aerospace components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A field programmable gate array-based timing and control system for the dynamic compression sector

A field programmable gate array (FPGA)-based timing and trigger control system has been developed for the Dynamic Compression Sector (DCS) user facility located at the Advanced Photon Source (APS) at Argonne National Laboratory. The DCS is a first-of-its-kind capability dedicated to dynamic compression science. All components of the DCS laser shock station—x-ray choppers, single-shot shutter, internal laser triggers, and shot diagnostics—must be synchronized with respect to the arrival of x rays in the hutch. An FPGA synchronized to the APS storage ring radio frequency clock (352 MHz) generates trigger signals for each stage of the laser and x-ray shutter system with low jitter. The developed FPGA-based control system was the first system used to control the laser and the shutter system since its commissioning, and it has been developing since then to improve the timing jitter. The system is composed of a Zynq FPGA, a debug card, line drivers, and a power supply. The delay and offsets of the trigger signals can be adjusted by using a user-friendly graphical user interface with high precision. Here, the details of the system architecture, timing requirements, firmware, and software implementation along with the performance evaluation are presented in this paper. The system offers low timing jitter (15.5 ps rms) with respect to the APS 352 MHz clock, suitable for the 100 ps (FWHM) x-ray bunch duration at the APS.

47 OTHER INSTRUMENTATION↗

A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches

Phasor measurement unit (PMU) networks deliver accurate and timely measurements, which is essential for managing today’s electric power systems. To ensure data quality and enhance the cyber-resilience of PMU networks against malicious attacks and data errors, this study presents an online PMU missing data recovery scheme by leveraging P4 programmable switches. The data plane incorporates a customized PMU protocol parser that abstracts the necessary payload data for recovery. Recovery processes are executed in the control plane using a pre-trained machine learning model. Both traditional and advanced ML models, such as transformer and TimeGPT, are explicitly employed for data prediction. This approach ensures rapid and precise data recovery. Performance evaluations focus on recovery speed and accuracy, using a real dataset from a campus microgrid. With 20% missing PMU data, the mean absolute percentage error for voltage magnitude is 0.0384%, and the phase angle error discrepancy is approximately 0.4064%.

Phasor Measurement Unit, Machine Learning, Program↗

Programmable solar array simulator.

Operational and circuit features of laboratory device built to simulate dynamic electrical output characteristics of programmable solar array in orbital flight

ANALOG COMPUTER↗

Rapid evolution of analog circuits configured on a field programmable transistor array

The purpose of this paper is to illustrate evolution of analog circuits on a stand-alone board-level evolvable system (SABLES). SABLES is part of an effort to achieve integrated evolvable systems. SABLES provides autonomous, fast (tens to hundreds of seconds), on-chip circuit evolution involving about 100,000 circuit evaluations. Its main components are a JPL Field Programmable Transistor Array (FPTA) chip used as transistor-level reconfigurable hardware, and a TI DSP that implements the evolutionary algorithm controlling the FPTA reconfiguration. The paper details an example of evolution on SABLES and points out to certain transient and memory effects that affect the stability of solutions obtained reusing the same piece of hardware for rapid testing of individuals during evolution.

SABLES analog circuits field programmable transist↗

Qualification Strategies of Field Programmable Gate Arrays (FPGAs) for Space Application

This viewgraph document reviews the issue of using Field Programmable Gate Arrays (FPGAs) in Space Application, and the some of the strategies for qualifying the FPGA. Qualification and risk management of such complex systems requires new approaches. The paper presents a matrix approach to qualification has been presented that: - Complements historical specifications - Highlights the importance of device physics as a cornerstone to qualification. - Provides levels of risk management that expressly document trade offs. - Stresses the role of the FPGA vendor as team member in the development of modern spacecraft.

Mil Standard 883↗