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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Sampling Downconverter For Radio-Frequency Signals

Phase and delay errors reduced greatly. Proposed GaAs integrated-circuit for receiver of radio signals at gigahertz frequencies samples incoming signal in phase and in quadrature, digitizes it, and down-converts it to baseband in single step. Incorporates both digital and analog components in design offering improved stability, versatility, and sampling bandwidth. Eliminates need for several components found in conventional analog designs, including mixers, postmixer filters, and 90 degree phase shifter.

Thomas, J. B.↗
NASA NTRS2005

Effects of High-frequency Wind Sampling on Simulated Mixed Layer Depth and Upper Ocean Temperature

Effects of high-frequency wind sampling on a near-global ocean model are studied by forcing the model with a 12 hourly averaged wind product and its 24 hourly subsamples in separate experiments. The differences in mixed layer depth and sea surface temperature resulting from these experiments are examined, and the underlying physical processes are investigated. The 24 hourly subsampling not only reduces the high-frequency variability of the wind but also affects the annual mean wind because of aliasing. While the former effect largely impacts mid- to high-latitude oceans, the latter primarily affects tropical and coastal oceans. At mid- to high-latitude regions the subsampled wind results in a shallower mixed layer and higher sea surface temperature because of reduced vertical mixing associated with weaker high-frequency wind. In tropical and coastal regions, however, the change in upper ocean structure due to the wind subsampling is primarily caused by the difference in advection resulting from aliased annual mean wind, which varies with the subsampling time. The results of the study indicate a need for more frequent sampling of satellite wind measurement and have implications for data assimilation in terms of identifying the nature of model errors.

mixed layered depth↗
NASA NTRS1994

Performance evaluation of digital phase-locked loops for advanced deep space transponders

The performances of the digital phase-locked loops (DPLL's) for the advanced deep-space transponders (ADT's) are investigated. DPLL's considered in this article are derived from the analog phase-locked loop, which is currently employed by the NASA standard deep space transponder, using S-domain to Z-domain mapping techniques. Three mappings are used to develop digital approximations of the standard deep space analog phase-locked loop, namely the bilinear transformation (BT), impulse invariant transformation (IIT), and step invariant transformation (SIT) techniques. The performance in terms of the closed loop phase and magnitude responses, carrier tracking jitter, and response of the loop to the phase offset (the difference between in incoming phase and reference phase) is evaluated for each digital approximation. Theoretical results of the carrier tracking jitter for command-on and command-off cases are then validated by computer simulation. Both theoretical and computer simulation results show that at high sampling frequency, the DPLL's approximated by all three transformations have the same tracking jitter. However, at low sampling frequency, the digital approximation using BT outperforms the others. The minimum sampling frequency for adequate tracking performance is determined for each digital approximation of the analog loop. In addition, computer simulation shows that the DPLL developed by BT provides faster response to the phase offset than IIT and SIT.

Nguyen, T. M.↗
NASA NTRS1993

Airborne measurements of sulfur dioxide, dimethyl sulfide, carbon disulfide, and carbonyl sulfide by isotope dilution gas chromatography/mass spectrometry

A gas chromatograph/mass spectrometer is described for determining atmospheric sulfur dioxide, carbon disulfide, dimethyl sulfide, and carbonyl sulfide from aircraft and ship platforms. Isotopically labelled variants of each analyte were used as internal standards to achieve high precision. The lower limit of detection for each species for an integration time of 3 min was 1 pptv for sulfur dioxide and dimethyl sulfide and 0.2 pptv for carbon disulfide and carbonyl sulfide. All four species were simultaneously determined with a sample frequency of one sample per 6 min or greater. When only one or two species were determined, a frequency of one sample per 4 min was achieved. Because a calibration is included in each sample, no separate calibration sequence was needed. Instrument warmup was only a few minutes. The instrument was very robust in field deployments, requiring little maintenance.

Bandy, Alan R.↗
NASA NTRS2024

Long-Term Groundwater Monitoring Report Industrial Area Kennedy Space Center, Florida

This report presents the 2023 groundwater sampling results from the National Aeronautics and Space Administration (NASA) Industrial Area (IA) Long-Term Monitoring (LTM) activities. Due to the project contract ending in 2023, this report presents one year of LTM activities instead of the two-year timeframe presented in previous reports. The NASA IA LTM Program includes the following 12 sites: - Ransom Road Landfill (RRLF) – Solid Waste Management Unit (SWMU) 003 - Building M7-0505 Treatment Tank Area (M505) – SWMU 039 - Operations and Checkout Building (O&C) – SWMU 076 - Vertical Processing Facility (VPF) – SWMU 077 - Environmental Health Facility (EHF) – SWMU 079 - Kennedy Athletic, Recreation, and Social Park 1 (KARS Park 1) – SWMU 084 - Engineering Development Laboratory (EDL) – SWMU 085 - Launch Equipment Test Facility (LETF) – SWMU 091 - Mobil Service Station (MOBIL) – SWMU 093 - General Services Administration Seized Property (GSSP) – SWMU 095 - Space Station Processing Facility (SSPF) – SWMU 098 - Fuel Storage Area #1 Underground Storage Tank [Building 1044] (FSA1) – Potential Release Location (PRL) 157 Sampling events for the IA LTM Program are conducted seasonally during the dry and wet seasons, which occur in May and November, respectively. The sites in the NASA IA LTM Program are sampled on annual, biennial, or 5-year sampling frequencies based on historical trends. The current sampling frequencies for the NASA IA LTM sites are as follows: - FSA1 is sampled annually, alternating between wet and dry seasons. - GSSP is sampled annually during the wet season. - Seven sites are sampled biennially, alternating between the wet and dry seasons (RRLF, M505, O&C, VPF, LETF, MOBIL, and SSPF). - EHF and EDL are sampled biennially during the wet season. - KARS Park 1 is sampled once every 5 years.

remediation↗
NASA NTRS1998

A Satellite Infrared Technique for Diurnal Rainfall Variability Studies

Reliable information on the distribution of precipitation at high temporal resolution (<l hour) is essential for understanding the characteristics of convection in a region. Cloud-top infrared (IR) brightness temperatures from geostationary platforms have a weak physical connection to precipitation, however, their high sampling frequency makes them attractive in studying the temporal evolution of cloudiness and convection. On the other hand, microwave-based (MW) observations from lower sampling-frequency polar-orbiting platforms can provide a better physical connection to precipitating hydrometeors. A recent invention in rainfall estimation from a combination of these two sensors involves adjustment of IR estimates using co-existing MW-based precipitation data on a monthly basis. These techniques use the MW data to remove systematic errors in IR rain estimates, while retaining the high sampling frequency of IR observations (approximately every 15-30 minutes). Perhaps of even greater importance to climate and hydrometeorological applications is the separation of mesoscale convective systems into a portion of rain associated with deep convection (hereafter called convective precipitation), and to precipitation falling from more widespread anvil clouds. This current work focuses on estimation of tropical convective and stratiform rainfall. We attempt to answer fundamental questions, such as : is estimation of convective and stratiform precipitation from IR feasible? If so, how accurate can this be? What is the scale dependence of the IR algorithm's performance? To address these questions, quantitative comparisons are performed between coincident IR- and MW-based instantaneous rainfall estimates at the MW 85 Ghz resolution (-12.5 km). Our data set spans a three-month period (January to March, 1996) of MW and IR observations over northern South America (15N-15S and 35W-80W), which includes the Amazon river basin.

Anagnostou, Emmanouil↗
DOE OSTI2024

LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry

Since their advent over 2 decades ago, autonomous Argo floats have revolutionized the field of oceanography, and, more recently, the addition of biogeochemical and biological sensors to these floats has greatly improved our understanding of carbon, nutrient, and oxygen cycling in the ocean. While Argo floats offer unprecedented horizontal, vertical, and temporal coverage of the global ocean, uncertainties remain about whether Argo sampling frequency and density capture the true spatiotemporal variability in physical, biogeochemical, and biological properties. As the true distributions of, e.g., temperature or oxygen are unknown, these uncertainties remain difficult to address with Argo floats alone. Numerical models with synthetic observing systems offer one potential avenue to address these uncertainties. Here, we implement synthetic biogeochemical Argo floats into the Energy Exascale Earth System Model version 2 (E3SMv2), which build on the Lagrangian In Situ Global High-Performance Particle Tracking (LIGHT) module in E3SMv2 (E3SMv2-LIGHT-bgcArgo-1.0). Since the synthetic floats sample the model fields at model run time, the end user defines the sampling protocol ahead of any model simulation, including the number and distribution of synthetic floats to be deployed, their sampling frequency, and the prognostic or diagnostic model fields to be sampled. Using a 6-year proof-of-concept simulation, we illustrate the utility of the synthetic floats in different case studies. In particular, we quantify the impact of (i) sampling density on the float-derived detection of deep-ocean change in temperature or oxygen and on float-derived estimates of phytoplankton phenology, (ii) sampling frequency and sea-ice cover on float trajectory lengths and hence float-derived estimates of current velocities, and (iii) short-term variability in ecosystem stressors on estimates of their seasonal variability.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Design of FIR digital filters for pulse shaping and channel equalization using time-domain optimization

Three algorithms are developed for designing finite impulse response digital filters to be used for pulse shaping and channel equalization. The first is the Minimax algorithm which uses linear programming to design a frequency-sampling filter with a pulse shape that approximates the specification in a minimax sense. Design examples are included which accurately approximate a specified impulse response with a maximum error of 0.03 using only six resonators. The second algorithm is an extension of the Minimax algorithm to design preset equalizers for channels with known impulse responses. Both transversal and frequency-sampling equalizer structures are designed to produce a minimax approximation of a specified channel output waveform. Examples of these designs are compared as to the accuracy of the approximation, the resultant intersymbol interference (ISI), and the required transmitted energy. While the transversal designs are slightly more accurate, the frequency-sampling designs using six resonators have smaller ISI and energy values.

Houts, R. C.↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was 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.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Cartesian Mesh Simulations for the Third AIAA Sonic Boom Prediction Workshop

Simulation results are presented for all cases from the Third AIAA Sonic Boom Prediction Workshop. An inviscid, embedded-boundary Cartesian-mesh flow solver is used in conjunction with adjoint-based mesh adaptation to compute nearfield pressure signatures. Specialized techniques are applied to maximize accuracy and minimize cost on Cartesian meshes. The Richardson-based error estimate highlights regions of the signatures most sensitive to mesh refinement. Timing results and coarse, medium, and fine mesh sizes for nearfield cases demonstrate that the parallel decomposition approach is efficient in both computational time and wall-clock. Pressure signals are propagated to the ground using an augmented Burgers’ equation solver to predict boom carpets. Ground signatures and loudness metrics are presented for a standard atmosphere as well as more realistic atmospheric profiles, which affect overall noise levels and can significantly widen the boom carpet. Mesh convergence studies show that high sampling frequencies, around 500 kHz, are required for propagation, and the sampling frequency increases at large off-track angles with longer acoustic ray paths and propagation times. The numerical methods yield accurate results for predicting low sonic boom signatures while being among the least computationally expensive of the workshop.

ARMD↗
DOE OSTI2020

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Moire patterns and two-dimensional aliasing in line scanner data acquisition systems

The basic mechanism underlying the generation of Moire patterns in line scanner data acquisition systems is examined. A general expression is developed in terms of typical system parameters for the reproduced image of such systems and the interaction of the image spectrum; the raster frequency and digital sampling frequency of the A/D conversion process are discussed and examples given. Systems design requirements for avoiding Moire pattern generation and two-dimensional aliasing are discussed.

Mcgillem, C. D.↗
NASA NTRS1974

Moire patterns and two-dimensional aliasing in line scanner data acquisition systems

The basic mechanism underlying the generation of Moire patterns in line scanner data acquisition systems is examined. A general expression is developed in terms of typical system parameters for the reproduced image of such systems and the interaction of the image spectrum; the raster frequency and digital sampling frequency of the A/D conversion process are discussed and examples given. System design requirements for avoiding Moire pattern generation and two-dimensional aliasing are discussed.

Mcgillem, C. D.↗
NASA NTRS1993

Measurements of atmospheric dimethylsulfide, hydrogen sulfide, and carbon disulfide during GTE/CITE 3

Measurements of atmospheric dimethylsulfide (DMS), hydrogen sulfide (H2S), and carbon disulfide (CS2) were made over the North and South Atlantic Ocean as part of the Global Tropospheric Experiment/Chemical Instrumentation Test and Evaluation (GTE/CITE 3) project. DMS and CS2 samples were collected and analyzed using an automated gas chromatography/flame photometric detection system with a sampling frequency of 10 min. H2S samples were collected using silver nitrate impregnated filters and analyzed by fluorescence quenching. The DMS data from both hemispheres have a bimodal distribution. Over the North Atlantic this reflects the difference between marine and continental air masses. Over the South Atlantic it may reflect differences in the sea surface source of DMS, corresponding to different air mass source regions. The median boundary layer H2S and CS2 levels were significantly higher in the northern hemisphere than the southern hemisphere, reflecting the higher frequency of samples influenced by pollutant and/or coastal emissions. Composite vertical profiles of DMS and H2S are similar to each other, are consistent with a sea surface source. Vertical profiles of CS2 have maxima in the free troposphere, implicating a continental source. The low levels of H2S and CS2 found in the southern hemisphere constrain the role of these compounds in global budgets to significantly less than previously estimated.

Cooper, David J.↗
NASA NTRS1973

Optimal space communications techniques

The design, development, and analysis are reported of a digital phase-locked loop (DPLL) for FM demodulation and threshold extension. One of the features of the developed DPLL is its synchronous, real time operation. The sampling frequency is constant and all the required arithmetic and logic operations are performed within one sampling period, generating an output sequence which is converted to analog form and filtered. An equation relating the sampling frequency to the carrier frequency must be satisfied to guarantee proper DPLL operation. The synchronous operation enables a time-shared operation of one DPLL to demodulate several FM signals simultaneously. In order to obtain information about the DPLL performance at low input signal-to-noise ratios, a model of an input noise spike was introduced, and the DPLL equation was solved using a digital computer. The spike model was successful in finding a second order DPLL which yielded a five db threshold extension beyond that of a first order DPLL.

Schilling, D. L.↗
NASA NTRS1986

Chaotic rotation of Hyperion?

Thomas et al. (1984) analyzed 14 Voyager 2 images of Saturn's satellite Hyperion and interpreted them to be consistent with a coherent (nonchaotic) rotation period of 13.1 days. This interpretation was criticized by Peale and Wisdom (1984), who argued that the low sampling frequency of Voyager data does not allow chaotic or nonchaotic rotation to be distinguished. New observations obtained with a higher sampling frequency are reported here which conclusively show that the 13.1 day period found by Thomas et al. was not due to coherent rotation.

Binzel, R. P.↗
NASA NTRS2008

Systems and methods for self-synchronized digital sampling

Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

Samson, Jr., John R.↗
DOE OSTI2023

High-bandwidth image-based predictive laser stabilization via optimized Fourier filters

Controlling the delivery of kHz-class pulsed lasers is of interest in a variety of industrial and scientific applications, from next-generation laser-plasma acceleration to laser-based x-ray emission and high-precision manufacturing. The transverse position of the laser pulse train on the application target is often subject to fluctuations by external drivers (e.g., room cooling and heating systems, motorized optics stages and mounts, vacuum systems, chillers, and/or ground vibrations). For typical situations where the disturbance spectrum exhibits discrete peaks on top of a broad-bandwidth lower-frequency background, traditional PID (proportional-integral-derivative) controllers may struggle, since as a general rule PID controllers can be used to suppress vibrations up to only about 5%–10% of the sampling frequency. Here, a predictive feed-forward algorithm is presented that significantly enhances the stabilization bandwidth in such laser systems (up to the Nyquist limit at half the sampling frequency) by online identification and filtering of one or a few discrete frequencies using optimized Fourier filters. Furthermore, the system architecture demonstrated here uses off-the-shelf CMOS cameras and piezo-electric actuated mirrors connected to a standard PC to process the alignment images and implement the algorithm. To avoid high-end, high-cost components, a machine-learning-based model of the piezo mirror’s dynamics was integrated into the system, which enables high-precision positioning by compensating for hysteresis and other hardware-induced effects. A successful demonstration of the method was performed on a 1 kHz laser pulse train, where externally-induced vibrations of up to 400 Hz were attenuated by a factor of five, far exceeding what could be done with a standard PID scheme.

Natal, Joseph↗