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At least 721 records · Page 40

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.

Mosher, Alexander [Fermilab]↗

Upgrades to Common Data Acquisition System Software Development for NASA's Rocket Propulsion Test Facilities and Software Reuse

Approximately five years ago, the National Aeronautics and Space Administration (NASA) Stennis Space Center (SSC) resumed operation of its large rocket engine test facilities after thirty years of contractor control. During this period, contactors used their own proprietary Data Acquisition System (DAS) to record and process rocket propulsion test data. The transition from a contractor managed facility to a NASA managed facility posed a difficult challenge. In order to support the commercial space launch initiative, SSC needed to develop a software replacement for the contractor proprietary DAS. This replacement software would enable SSC to operate propulsion test facilities more cost effectively and to be more readily able to adapt software for reuse, while at the same time provide internal and external customers with reliable population test data. Therefore, SSC developed in-house, a non-proprietary software suite of applications to replace the previously used proprietary DAS. The requirements for the DAS suite included recording and processing propulsion test data. This capability eliminates the necessity for customers to provide a DAS or rely on a competitor's DAS. An additional benefit of owning the software suite included enabling the ability to add additional features and functionality at a lower cost. The Rocket Propulsion Test (RPT) Program Office reviewed consideration for funding this project with the caveat that development of the software included availability for use with minimal modifications to all SSC test facilities and RPT centers: Marshall Space Flight Center (MSFC), White Sands Test Facility (WSTF), and Glenn Research Center (GRC) Plum Brook Station. Based upon this guideline, SSC created the NASA Data Acquisition System (NDAS) software suite. The ability to use the software at multiple centers, even though each field center uses differing DAS hardware with different capabilities, drove a requirement that the software design be portable with minimal modifications to the software. Then, with software release requirements, evaluations, and approvals completed, the NDAS software suite could also become available to other government agencies, corporations, universities, and the general United States public.

Herbert, Phillip W., Sr.↗

CHESS 2025: Waveform LiDAR data from NEON AOP surveys

This dataset provides Level 1 (L1) full-waveform light detection and ranging (LiDAR) data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. Waveform LiDAR data can provide more detailed information about objects on the ground than discrete point clouds typically do, and they are often used for granular target segmentation and characterization of subcanopy vegetation. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary waveform LiDAR data delivered by NEON and are provided per flightline in compressed Pulsewaves format, an open-source binary file standard. A Pulsewaves object comprises a two files: a pulse (.pls) file, which stores the geographic origin, outgoing vector, and metadata for every laser pulse emitted by the scanner, and a wave file (.wvs), which stores the sequential amplitude samples of the outgoing pulse and the returning signals. The files are published here in their compressed forms (.plz, .wvz). All waveform data were processed following the theoretical workflow described in the NEON L0-to-L1 Waveform LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022a); however, the Pulsewaves output format differs from a legacy format described in that document. Waveform amplitude samples are recorded at 1 nanosecond intervals. All coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Waveform data for the UPTA survey area were collected without incident and the published records are complete. However, both the ALMO and CRBU collections experienced issues that resulted in incomplete data for those areas. On collection day 2018-06-16 a hardware failure caused the waveform digitizer to lose data from the eastern edge of the ALMO site (Figure 22). The waveform data for flightlines 2–20 could not be extracted from the digitizer, and the data proved unrecoverable. As a result, a portion of the site does not have coverage with waveform data. Although no hardware failure was observed during collection over the CRBU area, final waveform files generated by vendor software contained only ~25% of the expected number of return pulses. After discovery, NEON initiated troubleshooting with the vendor. The root cause of the data ablation had not been identified at the time of publication. Additional data will be published in an update to this package if further recovery proves successful. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data

We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface and command-line tool for high-dimensional mass spectrometry data analysis workflows, offering ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation: algorithm implementations utilize all dimensions simultaneously to (i) offer greater separation between features, improving detection sensitivity, (ii) increase alignment/feature matching confidence among datasets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS data, demonstrating the advantages of a multidimensional approach in each data processing step.

Colby, Sean M↗

An application of fuzzy sets in real time filtering problems

The human decision-making task is modeled with fuzzy sets and the Kalman filter updates to the state vector are weighted using fuzzy functions. Results of the study show that the use of fuzzy set models gives results comparable to those requiring human assistance, e.g. lock on to false targets, and better results when the problem is caused by noise and/or bias, or unexpected errors in the state vector at initial acquisition.

Lea, Robert N.↗

Remote noncontacting measurements of heat transfer coefficients for detection of boundary layer transition in wind tunnel tests

An infrared measurement system is used that consists of a laser heating source, an infrared camera for data acquisition, and a video recorder for data storage. A laser beam is scanned over an airfoil, heating its surface to a few degrees above ambient. An infrared camera then measures the temperature of the airfoil over a two-dimensional field, and these temperatures are stored as a function of time on a video recorder. The resulting temperature pictures are digitized and an iterative approximation algorithm is used to extract the heat transfer coefficient. The resulting values are normalized to the natural convection condition. The technique has been applied in low-speed wind tunnel tests and compared to well-established hot-film measurements which were made simultaneously to confirm the flow conditions. Heat transfer coefficients were determined using a linear scanning pattern, to indicate the position of natural and of artificially induced transition on an airfoil, at various wind speeds. The technique is shown to be sensitive to transition at low Mach numbers. The advantages of the technique are discussed.

Heath, D. Michele↗

A Digital Control Algorithm for Magnetic Suspension Systems

An ongoing program exists to investigate and develop magnetic suspension technologies and modelling techniques at NASA Langley Research Center. Presently, there is a laboratory-scale large air-gap suspension system capable of five degree-of-freedom (DOF) control that is operational and a six DOF system that is under development. Those systems levitate a cylindrical element containing a permanent magnet core above a planar array of electromagnets, which are used for levitation and control purposes. In order to evaluate various control approaches with those systems, the Generic Real-Time State-Space Controller (GRTSSC) software package was developed. That control software package allows the user to implement multiple control methods and allows for varied input/output commands. The development of the control algorithm is presented. The desired functionality of the software is discussed, including the ability to inject noise on sensor inputs and/or actuator outputs. Various limitations, common issues, and trade-offs are discussed including data format precision; the drawbacks of using either Direct Memory Access (DMA), interrupts, or program control techniques for data acquisition; and platform dependent concerns related to the portability of the software, such as memory addressing formats. Efforts to minimize overall controller loop-rate and a comparison of achievable controller sample rates are discussed. The implementation of a modular code structure is presented. The format for the controller input data file and the noise information file is presented. Controller input vector information is available for post-processing by mathematical analysis software such as MATLAB1.

Britton, Thomas C.↗

High-temperature Strain Sensor and Mounting Development

This report describes Government Work Package Task 29 (GWP29), whose purpose was to develop advanced strain gage technology in support of the National Aerospace Plane (NASP) Program. The focus was on advanced resistance strain gages with a temperature range from room temperature to 2000 F (1095 C) and on methods for reliably attaching these gages to the various materials anticipated for use in the NASP program. Because the NASP program required first-cycle data, the installed gages were not prestabilized or heat treated on the test coupons before first-cycle data were recorded. NASA Lewis Research Center, the lead center for GWP29, continued its development of the palladium-chromium gage; NASA Langley Research Center investigated a new concept gage using Kanthal A1; and the NASA Dryden Flight Research Center chose the well-known BCL-3 iron-chromium-aluminum gage. Each center then tested all three gages. The parameters investigated were apparent strain, drift strain, and gage factor as a function of temperature, plus gage size and survival rate over the test period. Although a significant effort was made to minimize the differences in test equipment between the three test sites (e.g., the same hardware and software were used for final data processing), the center employed different data acquisition systems and furnace configurations so that some inherent differences may be evident in the final results.

Williams, W. Dan↗

A Contextually Supervised Optimization-Based HVAC Load Disaggregation Methodology

This paper presents a novel contextually supervised optimization-based approach for disaggregating heating, ventilation, and air-conditioning (HVAC) loads using smart meter or Supervisory Control and Data Acquisition data. To disaggregate the load into HVAC loads, large and infrequently used loads (LIUL), and base loads, we formulate an optimization problem to minimize a set of five loss terms, consisting of the reconstruction errors of the overall load profile, the ramp rate losses, and three distinct loss functions linked with the HVAC load, base load, and LIUL, respectively. To enhance accuracy, we incorporate two forms of contextual information into the problem formulation. First, we utilize mutual information to estimate HVAC energy consumption. Second, we employ a base load dictionary to constrain HVAC load estimation errors. The obtained HVAC load profiles are fine-tuned by abnormal ramp detection followed by binary hypothesis testing. Here, the proposed method is developed and tested using sub-metered residential and commercial building data. Simulation results show that the proposed method outperforms existing methods across various data resolutions and load aggregation levels, showing excellent transferability and generalizability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

GridDS: Data Science Toolkit for Energy Grid Data

According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is

Ladd, Alexander↗

LSST Commissioning Camera

The LSST Commissioning Camera (LSSTComCam) was mounted on the Simonyi Survey Telescope in August 2022 and observed for seven weeks in late 2024 until it was removed from the telescope in December 2024. It is a smaller, fully functional version of LSSTCam, with only the central raft of 9 4k x 4k CCDs (all ITL sensors) and comprising 144 megapixels. Every CCD has 16 amplifiers, each reading 1 million pixels. LSSTComCam was designed to enable end-to-end testing of the observatory’s systems, including data acquisition, image processing, and observatory operations.

79 ASTRONOMY AND ASTROPHYSICS↗

Aircraft Lightning Electromagnetic Environment Measurement

This paper outlines a NASA project plan for demonstrating a prototype lightning strike measurement system that is suitable for installation onto research aircraft that already operate in thunderstorms. This work builds upon past data from the NASA F106, FAA CV-580, and Transall C-180 flight projects, SAE ARP5412, and the European ILDAS Program. The primary focus is to capture airframe current waveforms during attachment, but may also consider pre and post-attachment current, electric field, and radiated field phenomena. New sensor technologies are being developed for this system, including a fiber-optic Faraday polarization sensor that measures lightning current waveforms from DC to over several Megahertz, and has dynamic range covering hundreds-of-volts to tens-of-thousands-of-volts. A study of the electromagnetic emission spectrum of lightning (including radio wave, microwave, optical, X-Rays and Gamma-Rays), and a compilation of aircraft transfer-function data (including composite aircraft) are included, to aid in the development of other new lightning environment sensors, their placement on-board research aircraft, and triggering of the onboard instrumentation system. The instrumentation system will leverage recent advances in high-speed, high dynamic range, deep memory data acquisition equipment, and fiber-optic interconnect.

Ely, Jay J.↗

Deep Space Networking Experiments on the EPOXI Spacecraft

NASA's Space Communications & Navigation Program within the Space Operations Directorate is operating a program to develop and deploy Disruption Tolerant Networking [DTN] technology for a wide variety of mission types by the end of 2011. DTN is an enabling element of the Interplanetary Internet where terrestrial networking protocols are generally unsuitable because they rely on timely and continuous end-to-end delivery of data and acknowledgments. In fall of 2008 and 2009 and 2011 the Jet Propulsion Laboratory installed and tested essential elements of DTN technology on the Deep Impact spacecraft. These experiments, called Deep Impact Network Experiment (DINET 1) were performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. The DINET 1 software was installed on the backup software partition on the backup flight computer for DINET 1. For DINET 1, the spacecraft was at a distance of about 15 million miles (24 million kilometers) from Earth. During DINET 1 300 images were transmitted from the JPL nodes to the spacecraft. Then, they were automatically forwarded from the spacecraft back to the JPL nodes, exercising DTN's bundle origination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days. The first DINET 1 experiment successfully validated many of the essential elements of the DTN protocols. DINET 2 demonstrated: 1) additional DTN functionality, 2) automated certain tasks which were manually implemented in DINET 1 and 3) installed the ION SW on nodes outside of JPL. DINET 3 plans to: 1) upgrade the LTP convergence-layer adapter to conform to the international LTP CL specification, 2) add convergence-layer "stewardship" procedures and 3) add the BSP security elements [PIB & PCB]. This paper describes the planning and execution of the flight experiment and the validation results.

automated data communication↗

National Institute for Rocket Propulsion Systems 1st Annual Workshop

The National Institute for Rocket Propulsion Systems (NIRPS) is a Government -wide initiative that seeks to ensure the resiliency of the Nation fs rocket propulsion community in order for the enterprise to remain vibrant and capable of providing reliable and affordable propulsion systems for the nation fs defense, civil and commercial needs. Recognizing that rocket propulsion is a multi-use technology that ensures the nation fs leadership in aerospace, the Government has a vested interest in maintaining this strategic capability through coordinated and synchronized acquisition programs and continual investments in research and development. NIRPS is a resource for collaboration and integration between all sectors of the U.S. propulsion enterprise, supporting policy development options, identifying technology requirements, and offering solutions that maximize national resources while ensuring that capability exists to meet future demand. NIRPS functions as a multi ]agency organization that our nation fs decision makers can look to for comprehensive information regarding all issues concerning the propulsion enterprise.

Doreswamy, Rajiv↗

Real-Time Wireless Data Acquisition System

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Valencia, Emilio J.↗

Mitochondrial integration and ovarian cancer chemotherapy resistance

Ovarian cancer has been nicknamed the “silent killer”. Most patients with ovarian cancer are diagnosed at an advanced stage of the disease for the first time because of its insignificant early clinical symptoms. In addition to the difficulty of early screening and delay in diagnosis, the high recurrence rate and relapsed refractory status of patients with ovarian cancer are also important factors for their high mortality. Patients with recurrent ovarian cancer often use neoadjuvant chemotherapy followed by surgery as the first choice. However, this is often accompanied by chemotherapy resistance, leading to treatment failure and a mortality rate of more than 90%. In the past, it was believed that the anti-tumor effect of chemotherapeutics represented by cisplatin was entirely attributable to its irreversible damage to DNA, but current research has found that it can inhibit cell growth and cytotoxicity via nuclear and cytoplasmic coordinated integration. As an important hub and integration platform for intracellular signal communication, mitochondria are responsible for multiple key factors during tumor occurrence and development, such as metabolic reprogramming, acquisition of metastatic ability, and chemotherapy drug response. The role of mitochondria in ovarian cancer chemotherapy resistance is becoming increasingly recognized. In this review, we discuss the cellular interactive regulatory network surrounding mitochondria, elucidate the mechanisms of tumor cell survival under chemotherapy, and discuss potential means of interfering with mitochondrial function as a novel anti-cancer therapy.

60 APPLIED LIFE SCIENCES↗

Development of a new computer system for aircraft noise prediction

The paper presents an overview of the activities of NASA's Aircraft Noise Prediction Office (ANOPO). The principal goal of ANOPO is to develop a comprehensive, user-oriented, Aircraft Noise Prediction Program (ANOPP). ANOPO's activities in support of ANOPP development are briefly discussed. They include acquisition, implementation, and evaluation of an in-house, interim collection of programs and implementation of a plan for acquiring, in the form of Key Technology Documents, state-of-the-art methodology for aircraft noise prediction. The paper is primarily devoted to a presentation of the general architecture and functional capability planned for ANOPP together with the rationale supporting major design decisions.

Raney, J. P.↗