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Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗

Sample Acquisition and Instrument Deployment (SAID)

This report details the interim progress for contract NASW-4818, Sample Acquisition and Instrument Deployment (SAID), a robotic system for deploying science instruments and acquiring samples for analysis. The system is a conventional four degree of freedom manipulator 2 meters in length. A baseline design has been achieved through analysis and trade studies. The design considers environmental operating conditions on the surface of Mars, as well as volume constraints on proposed Mars landers. Control issues have also been studied, and simulations of joint and tip movements have been performed. A passively braked shape memory actuator with the ability to measure load has been developed. The wrist also contains a mechanism which locks the lid output to the bucket so that objects can be grasped and released for instrument deployment. The wrist actuator has been tested for operational power and mechanical functionality at Mars environmental conditions. The torque which the actuator can produce has been measured. Also, testing in Mars analogous soils has been performed.

Boyd, Robert C.↗

On-the-Fly Mapping for Calibrating Directional Antennas

An improved method of calibrating a large directional radio antenna of the type used in deep-space communication and radio astronomy has been developed. This method involves a raster-scanning-and-measurement technique denoted on-the-fly (OTF) mapping, applied in consideration of the results of a systematic analysis of the entire measurement procedure. Phenomena to which particular attention was paid in the analysis include (1) the noise characteristics of a total-power radiometer (TPR) that is used in the measurements and (2) tropospherically induced radiometer fluctuations. The method also involves the use of recently developed techniques for acquisition and reduction of data. In comparison with prior methods used to calibrate such antennas, this method yields an order-of-magnitude improvement in the precision of determinations of antenna aperture efficiency, and improvement by a factor of five or more in the precision of determination of pointing error and beam width. Prerequisite to a meaningful description of the present method is some background information concerning three aspects of the problem of calibrating an antenna of the type in question: In OTF mapping measurements in which a TPR is used, the desired data are the peak temperature corresponding to a radio source, the pointing offset when the antenna is commanded to point toward the source, and the shape of the main lobe of the antenna beam, all as functions of the antenna beam elevation and azimuth angles. These data enable one to calculate the (1) antenna aperture efficiency by comparing the measured peak temperature with that expected for a 100-percent-efficient antenna, (2) the mechanical pointing error resulting from small misalignments of various parts of the antenna structure, and (3) misalignments of the antenna subreflector and other mirrors. For practical reasons having to do with obtaining adequate angular resolution and all-sky coverage, it is necessary to perform azimuth and elevation scans fairly rapidly. Many natural radio sources used in calibrating antennas are only approximately pointlike: some sources subtend angles greater than the beam width of a given antenna. In such a case, the antenna partially resolves the source structure and does not collect all of the radiation emitted by the source. This makes it necessary to estimate how much of the total known radiation from the source would actually be collected by the antenna if it were 100-percent efficient. The resulting estimate, leading to a source-size correction factor, introduces another degree of uncertainty to the measurements. OTF mapping can remove this uncertainty

Rochblatt, David↗

Development of a High Throughput PCIe Card for DAQ System in the ATLAS and DUNE Experiments

In the Run 3 upgrade of ATLAS experiment, the FELIX (Front-End LInk eXchange) system has been prepared as the interface between front-end electronics and common Data Acquisition (DAQ) systems. Based on a PCIe card hosted in commodity server, FELIX's flexibilty makes it has also been adopted by other experiments, such as the Single-Phase ProtoDUNE (Prototype for the Deep Underground Neutrino Experiment), sPHENIX and CBM experiments. The same PCIe based architecture is proposed for use in the ATLAS HL-LHC (High Luminosity Large Hadron Collider) upgrade and the DUNE experiment. To this end, the next generation of FELIX I/O card FLX-801 has been developed. It supports 25+ Gbps high speed fiber optical links and 16-lane Gen4 PCIe interface. There is an on-card DDR4 module to buffer event data for DUNE experiment. This paper reports on the test results for the demonstrator of this next generation card, with which main functions have been successfully evaluated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The False Dilemma: Rethinking AF Science and Technology Officer Talent Management

In 2019, Secretary of the Air Force (SECAF) Heather Wilson launched the 2030 Science and Technology (S&T) Strategy by stating, “The advantage will go to those who create the best technologies and who integrate and field them in creative operational ways that provide military advantages.” In 2021, 15% of Air Force general officers responsible for creating and integrating this technological edge had a science, technology, engineering, and math (STEM) graduate degree, and less than 1% of generals had a STEM doctorate. As one point of comparison, at least 32% and 13% of founding CEOs of Fortune 500 technology companies had a master’s and doctoral STEM degree, respectively. The gulf is larger when you consider that these CEOs used their technical degrees throughout their careers whereas most general officers do not. In large organizations, if the leader does not possess technical knowledge, it is difficult to drive innovation systems and connect ideas to reality. The evidence for this disconnect is abundant in acquisition challenges for high-tech systems, significant pushback to the “revolution in military affairs”, and failure of the “Third Offset” to take hold and deliver capabilities to offset Chinese and Russian capabilities. Indeed, when the former Air Force and Space Force Chief Software Officer, Nicolas M. Chaillan, offered his resignation, one of the main reasons for leaving was “the failure of OSD and the Joint Staff to deliver on their own alleged top ‘priority’, JADC2 – they couldn’t ‘walk the walk.’” Senior leaders have recognized this disconnect, and several inquiries and studies regarding STEM competency have been conducted. Many have posed a false dilemma: a large, STEM-cognizant or small, STEM-expert force. However, current and future STEM human capital needs are managed at the unit and functional area level. This leads to “silos” and the tactical “needs of the present” dominating the strategic “needs of the future”, highlighted by only two functional areas systematically tracking future STEM needs. Therefore, the decision on force structure appears to have been historically made by default through these and other perceived structural realities, and a vast majority of recommendations have focused on the small STEM community – an exercise in diminishing returns. In essence, the solution often boils down to finding unicorns – officers that have chartered the unforgiving pathway through the traditional “gates” to general officer while obtaining sufficient STEM proficiency along the way. Fortunately for the Air Force, these officers exist, albeit at a rate below what the evidence would suggest is necessary. However, this approach fundamentally limits the ability to develop a deep pool of officers with the ability to create and integrate technologies and ensures the Dunning-Kruger effect is prevalent. The Dunning-Kruger effect is a cognitive bias where those with limited knowledge in an area lack the expertise necessary to recognize their lack of expertise and consequently are prone to overestimate their knowledge and performance. In short, we need less leaders overestimating their STEM knowledge and more with hard-earned STEM competency required to “walk the walk” to create and integrate technologies for military advantage. This will not be accomplished by restricting the emphasis to the traditional scientists and engineering (S&E) career fields – the pool, only 10% of line officers, and general officer progression is just too small. Fortunately, the recent SECAF’s Management Initiatives and Chief of Staff’s (CSAF) Action Orders, both containing emphasis on organic expertise to “accrue advantage in military-technological competition,” present an opportunity to truly develop a framework for the force of the future.

99 GENERAL AND MISCELLANEOUS↗

Cinematic reflectometry using QIKR, the quite intense kinetics reflectometer

The Quite Intense Kinetics Reflectometer (QIKR) will be a general-purpose, horizontal-sample-surface neutron reflectometer. Reflectometers measure the proportion of an incident probe beam reflected from a surface as a function of wavevector (momentum) transfer to infer the distribution and composition of matter near an interface. The unique scattering properties of neutrons make this technique especially useful in the study of soft matter, biomaterials, and materials used in energy storage. Exploiting the increased brilliance of the Spallation Neutron Source Second Target Station, QIKR will collect specular and off-specular reflectivity data faster than the best existing such machines. It will often be possible to collect complete specular reflectivity curves using a single instrument setting, enabling “cinematic” operation, wherein the user turns on the instrument and “films” the sample. Samples in time-dependent environments (e.g., temperature, electrochemical, or undergoing chemical alteration) will be observed in real time, in favorable cases with frame rates as fast as 1 Hz. Cinematic data acquisition promises to make time-dependent measurements routine, with time resolution specified during post-experiment data analysis. This capability will be deployed to observe such processes as in situ polymer diffusion, battery electrode charge–discharge cycles, hysteresis loops, and membrane protein insertion into lipid layers.

47 OTHER INSTRUMENTATION↗

Effect of Flight on the Noise from Turbulent Jets in the Generalized Acoustic Analogy

This paper presents an extension of a noise prediction method for static jets based on the Generalized Acoustic Analogy to include a non-zero ambient stream to simulate the effects of flight. Extended formulae for the propagator functions, source terms and the far-field acoustic spectrum are derived. The formulations of the equation and the boundary conditions for numerical solution of the scalar adjoint Green’s function in the presence of a non-zero ambient stream are also given. Wherever possible, the corresponding equations in the original papers for the static case and their extensions to include a flight stream are identified. The extended formulation is implemented into an existing code and used to make predictions of the effect of the flight stream on the observed far-field noise for a series of subsonic, unheated, axisymmetric jets over a range of jet-exit and free-stream velocities using Reynolds-averaged Navier-Stokes flow solutions as input. The predictions are compared with data from experiments conducted at NASA Glenn Research Center which extend a fundamental jet noise database to include a flight stream of various speeds. Descriptions of the experimental setup, data acquisition, post-processing and corrections applied to account for the external shear-layer are given. It is shown that the acoustic analogy-based method can provide reasonably good predictions of the impact of an external flight stream on the spectral characteristics of noise from unheated round jets.

Jet noise↗

Effect of Flight on the Noise from Turbulent Jets in the Generalized Acoustic Analogy

This paper presents an extension of a noise prediction method for static jets based on the Generalized Acoustic Analogy to include a non-zero ambient stream to simulate the effects of flight. Extended formulae for the propagator functions, source terms and the far-field acoustic spectrum are derived. The formulations of the equation and the boundary conditions for numerical solution of the scalar adjoint Green’s function in the presence of a non-zero ambient stream are also given. Wherever possible, the corresponding equations in the original papers for the static case and their extensions to include a flight stream are identified. The extended formulation is implemented into an existing code and used to make predictions of the effect of the flight stream on the observed far-field noise for a series of subsonic, unheated, axisymmetric jets over a range of jet-exit and free-stream velocities using Reynolds-averaged Navier-Stokes flow solutions as input. The predictions are compared with data from experiments conducted at NASA Glenn Research Center which extend a fundamental jet noise database to include a flight stream of various speeds. Descriptions of the experimental setup, data acquisition, post-processing and corrections applied to account for the external shear-layer are given. It is shown that the acoustic analogy-based method can provide reasonably good predictions of the impact of an external flight stream on the spectral characteristics of noise from unheated round jets.

Jet noise↗

Effect of Flight on the Noise from Turbulent Jets in the Generalized Acoustic Analogy

This presents an extension of a noise prediction method for static jets based on the Generalized Acoustic Analogy to include a non-zero ambient stream to simulate the effects of flight. Extended formulae for the propagator functions, source terms and the far-field acoustic spectrum are derived. The formulations of the equation and the boundary conditions for numerical solution of the scalar adjoint Green’s function in the presence of a non-zero ambient stream are also given. Wherever possible, the corresponding equations in the original papers for the static case and their extensions to include a flight stream are identified. The extended formulation is implemented into an existing code and used to make predictions of the effect of the flight stream on the observed far-field noise for a series of subsonic, unheated, axisymmetric jets over a range of jet-exit and free-stream velocities using Reynolds-averaged Navier-Stokes flow solutions as input. The predictions are compared with data from experiments conducted at NASA Glenn Research Center which extend a fundamental jet noise database to include a flight stream of various speeds. Descriptions of the experimental setup, data acquisition, post-processing and corrections applied to account for the external shear-layer are given. It is shown that the acoustic analogy-based method can provide reasonably good predictions of the impact of an external flight stream on the spectral characteristics of noise from unheated round jets.

Jet noise↗

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

Miniature Intelligent Sensor Module

An electronic unit denoted the Miniature Intelligent Sensor Module performs sensor-signal-conditioning functions and local processing of sensor data. The unit includes four channels of analog input/output circuitry, a processor, volatile and nonvolatile memory, and two Ethernet communication ports, all housed in a weathertight enclosure. The unit accepts AC or DC power. The analog inputs provide programmable gain, offset, and filtering as well as shunt calibration and auto-zeroing. Analog outputs include sine, square, and triangular waves having programmable frequencies and amplitudes, as well as programmable amplitude DC. One innovative aspect of the design of this unit is the integration of a relatively powerful processor and large amount of memory along with the sensor-signalconditioning circuitry so that sophisticated computer programs can be used to acquire and analyze sensor data and estimate and track the health of the overall sensor-data-acquisition system of which the unit is a part. The unit includes calibration, zeroing, and signalfeedback circuitry to facilitate health monitoring. The processor is also integrated with programmable logic circuitry in such a manner as to simplify and enhance acquisition of data and generation of analog outputs. A notable unique feature of the unit is a cold-junction compensation circuit in the back shell of a sensor connector. This circuit makes it possible to use Ktype thermocouples without compromising a housing seal. Replicas of this unit may prove useful in industrial and manufacturing settings - especially in such large outdoor facilities as refineries. Two features can be expected to simplify installation: the weathertight housings should make it possible to mount the units near sensors, and the Ethernet communication capability of the units should facilitate establishment of communication connections for the units.

Beech, Russell S.↗

Design, Development and Test Challenges: Separation Mechanisms for the Orion Pad Abort-1 Flight Test

On May 6, 2010, NASA launched the first successful integrated flight test, Pad Abort-1, of the Orion Project from the White Sands Missile Range in Las Cruces, New Mexico. This test demonstrated the ability to perform an emergency pad abort of a full-scale 4.8 m diameter, 8200 kg crew capsule. During development of the critical separation mechanisms for this flight test, various challenges were overcome related to environments definition, installation complications, separation joint retraction speed, thruster ordnance development issues, load path validation and significant design loads increases. The Launch Abort System retention and release (LAS R&R) mechanism consisted of 6 discrete structural connections between the LAS and the crew module (CM) simulator, each of which had a preloaded tension tie, Superbolt torque-nut and frangible nut. During the flight test, the frangible nuts were pyrotechnically split, permitting the CM to separate from the LAS. The LAS separation event was the driving case in the shock environment for many co-located hardware items. During development testing, it was necessary to measure the source shock during the separation event so the predicted shock environment could be validated and used for certification testing of multiple hardware items. The Lockheed Martin test team measured the source separation shock due to the LAS R&R function, which dramatically decreased the predicted environment by 90% at 100 Hz. During development testing a hydraulic tensioner was used to preload the joint; however, the joint relaxation with the tensioner proved unsatisfactory so the design was modified to include a Superbolt torque-nut. The observed preload creep during lab testing was 4% after 30 days, with 2.5% occurring in the first 24 hours. The conversion of strain energy (preload) to kinetic energy (retraction) was measured to be 50-75%. Design features and careful monitoring of multiple strain gauges on each tension tie allowed a pure tensile load to be applied after stacking at the launch pad. Following installation, preload in each joint was monitored for 24 hours. Due to unforeseen complications and the influence of temperature on the portable data acquisition system, the team encountered difficulty in tracking the joint relaxation. In some cases, bond-line failure of the strain gauges occurred.

Dinsel, Alison↗

Optical communications link design for the tracking and data acquisition system

The communications performances of laser intersatellite links for a future NASA data-relay system are analyzed, and block diagrams of necessary optical terminals are generated based on technology projected to be available by 1992. Direct-detection optical communications subsystems are selected to interconnect two geosynchronous (GEO) satellites separated by 160 deg along the GEO arc and to interconnect a low-earth-orbit (LEO) satellite and either of the GEO satellites. The terminal designs are based on power budget calculations performed for the various links with and without an optical background in either the receiver or transmitter fields of view (FOVs). Optical antennas with 18-cm and 30-cm primary mirror diameters on the LEO and GEO satellites can achieve a 0.000001 average bit error rate during normal operations in each of the forward and return optical links with beginning-of-life (BOL) power margins of approximately 7 dB. With an optical background in the receiver FOV, communications in the GEO-GEO return link are interrupted, the LEO-GEO return link is undegraded, and the GEO-GEO and LEO-GEO forward links remain functional with reduced BOL power margins. With an optical background in the transmitter FOV, the GEO-GEO forward and return links are noticeably degraded, the LEO-GEO return link is only slightly degraded, and the LEO-GEO forward link remains undegraded.

Marshalek, R. G.↗

Real-time closed-loop simulation and upset evaluation of control systems in harsh electromagnetic environments

Digital control systems for applications such as aircraft avionics and multibody systems must maintain adequate control integrity in adverse as well as nominal operating conditions. For example, control systems for advanced aircraft, and especially those with relaxed static stability, will be critical to flight and will, therefore, have very high reliability specifications which must be met regardless of operating conditions. In addition, multibody systems such as robotic manipulators performing critical functions must have control systems capable of robust performance in any operating environment in order to complete the assigned task reliably. Severe operating conditions for electronic control systems can result from electromagnetic disturbances caused by lightning, high energy radio frequency (HERF) transmitters, and nuclear electromagnetic pulses (NEMP). For this reason, techniques must be developed to evaluate the integrity of the control system in adverse operating environments. The most difficult and illusive perturbations to computer-based control systems that can be caused by an electromagnetic environment (EME) are functional error modes that involve no component damage. These error modes are collectively known as upset, can occur simultaneously in all of the channels of a redundant control system, and are software dependent. Upset studies performed to date have not addressed the assessment of fault tolerant systems and do not involve the evaluation of a control system operating in a closed-loop with the plant. A methodology for performing a real-time simulation of the closed-loop dynamics of a fault tolerant control system with a simulated plant operating in an electromagnetically harsh environment is presented. In particular, considerations for performing upset tests on the controller are discussed. Some of these considerations are the generation and coupling of analog signals representative of electromagnetic disturbances to a control system under test, analog data acquisition, and digital data acquisition from fault tolerant systems. In addition, a case study of an upset test methodology for a fault tolerant electromagnetic aircraft engine control system is presented.

Belcastro, Celeste M.↗

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗

Colistin resistance plasmids dually enhance bacterial virulence and antibiotic resistance via surface polysaccharide biosynthesis

Plasmids carrying the mobilized colistin-resistance gene mcr-1 are prevalent among multidrug-resistant Gram-negative pathogens, yet their broad impact on bacterial physiology and virulence remains unclear. Here, we demonstrate that acquisition of an mcr-1 plasmid concurrently increases antimicrobial resistance and pathogenicity in Escherichia coli. On the same plasmid, the XRE-family transcriptional regulator EcaR cooperates with MCR-1 to activate the wec operon, driving biosynthesis of two surface polysaccharides: enterobacterial common antigen (ECA) and a high-molecular-weight O-chain. Expression of these surface polysaccharides increases bile resistance and virulence in a murine model and further elevates colistin resistance. MCR-1 enhances transcription of upstream genes in the wec operon, whereas EcaR directly activates an internal promoter (PwecE) to induce downstream gene expression. Thus, both components are required for surface polysaccharide expression, and deletion of either abolishes the phenotype. Genomic analysis of publicly available mcr plasmids reveals widespread co-occurrence of mcr-1 and ecaR on IncI2 and IncX4 plasmids, indicating their functional complementarity. These findings uncover a mechanism by which resistance plasmids remodel the bacterial surface, linking horizontal gene transfer to coordinated regulation of antimicrobial resistance and virulence.

Antimicrobial resistance↗