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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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At least 343 records · Page 19

Impact Mediated Loading Cytoplasmic Loading of Macromolecules into Adherent Cells

The advent of modern molecular biology, including the development of gene array technologies, has resulted in an explosion of information concerning the specific genes activated during normal cellular development, as well as those associated with a variety of pathological conditions. These techniques have served as a highly efficient, broacI.-based screening approach for those specific genes involved. in regulating normal cellular physiology and identifying candidate genes directly associated with the etiology of specific disease states. However, this approach provides information at the transcriptional' level only and does not necessarily indicate . that the gene in question is in fact translated i~to a protein, or whether or not post-translational modification of the protein occurs. The critical importance of post-translational modification (i.e. phosphorylation, glycosylation, sialyation, etc.) to protein function has been recognized with regard to a number of proteins involved in a variety of important disease states. For example, altered glycosylation of beta-amyloid precursor protein results in an increase in the amount of beta-amyloid peptide generated and hence secreted as insoluble extracellular amyloid deposits (Georgopoulou, McLaughlin et al. 2001; Walter, Fluhrer et al. 2001), a pathological hal1~nark of Alzheimer's disease. Abnormal phosphoryla~ion of synapsin I has been linked to alterations in synaptic vesicle trafficking leading to defective neurotransmission in Huntington's disease (Lievens, Woodman et al. 2002). Altered phosphorylation of the TAU protein involved in microtubule function has been linked to a number of neurodegenative diseases such as Alzheimer's disease (Billingsley and Kincaid 1997; Sanchez, Alvarez-T~llada et a1. 2001). Aberrant siaIyation of cell/I surface antigens has been detected in a number of different tumor cell types and has been linked to the acquisition of a neoplastic phenotype (Sell 1990), while improper' sia1yation of sodium channels in cardiac tissue has been linked to heart failure (Ufret-Vincenty, Baro et al. 2001; Fozzard and Kyle 2002).

Clarke, Mark S. F.↗

RTAPS (Research and Technology for Aerospace Propulsion Systems): Simulation of Structural Loads within a Hybrid Gear Resulting From Loading at the Gear Teeth

This report investigates the practical usage of hybrid structures for rotorcraft gearing. The primary driver for utilizing hybrid structures for rotorcraft gearing is to reduce the drive system weight. The hybrid structure concept featured in this study for rotorcraft gearing consists of a metallic gear tooth-rim, a web section manufactured from composite materials, and a metallic hub. The metallic gear tooth-rim is manufactured from conventional gear steel alloys, such as AISI 9310. The gear tooth-rim attaches to the outer diameter of the web section made from composite materials. The inner diameter of the composite web can then attach to a metallic hub, completing the assembly. It is assumed that areas of the shafting or hub where rolling element bearings may ride must remain as gear steel alloys for this study.

Hybrid Structures↗

RTAPS (Research and Technology for Aerospace Propulsion Systems): Simulation of Structural Loads within a Hybrid Gear Resulting From Loading at the Gear Teeth

This report investigates the practical usage of hybrid structures for rotorcraft gearing. The primary driver for utilizing hybrid structures for rotorcraft gearing is to reduce the drive system weight. The hybrid structure concept featured in this study for rotorcraft gearing consists of a metallic gear tooth-rim, a web section manufactured from composite materials, and a metallic hub. The metallic gear tooth-rim is manufactured from conventional gear steel alloys, such as AISI 9310. The gear tooth-rim attaches to the outer diameter of the web section made from composite materials. The inner diameter of the composite web can then attach to a metallic hub, completing the assembly. It is assumed that areas of the shafting or hub where rolling element bearings may ride must remain as gear steel alloys for this study.

Naffin, Richard K.↗

Assessment of New Load Schedules for the Machine Calibration of a Force Balance

New load schedules for the machine calibration of a six-component force balance are currently being developed and evaluated at the NASA Ames Balance Calibration Laboratory. One of the proposed load schedules is discussed in the paper. It has a total of 2082 points that are distributed across 16 load series. Several criteria were applied to define the load schedule. It was decided, for example, to specify the calibration load set in force balance format as this approach greatly simplifies the definition of the lower and upper bounds of the load schedule. In addition, all loads are assumed to be applied in a calibration machine by using the one-factor-at-a-time approach. At first, all single-component loads are applied in six load series. Then, three two-component load series are applied. They consist of the load pairs (N1, N2), (S1, S2), and (RM, AF). Afterwards, four three-component load series are applied. They consist of the combinations (N1, N2, AF), (S1, S2, AF), (N1, N2, RM), and (S1, S2, RM). In the next step, one four-component load series is applied. It is the load combination (N1, N2, S1, S2). Finally, two five-component load series are applied. They are the load combination (N1, N2, S1, S2, AF) and (N1, N2, S1, S2, RM). The maximum difference between loads of two subsequent data points of the load schedule is limited to 33 % of capacity. This constraint helps avoid unwanted load "jumps" in the load schedule that can have a negative impact on the performance of a calibration machine. Only loadings of the single- and two-component load series are loaded to 100 % of capacity. This approach was selected because it keeps the total number of calibration points to a reasonable limit while still allowing for the application of some of the more complex load combinations. Data from two of NASA's force balances is used to illustrate important characteristics of the proposed 2082-point calibration load schedule.

wind tunnel testing↗

Crane-Load Contact Sensor

An electronic instrument has been developed as a prototype of a portable crane-load contact sensor. Such a sensor could be helpful in an application in which the load rests on a base in a horizontal position determined by vertical alignment pins (see Figure 1). If the crane is not positioned to lift the load precisely vertically, then the load can be expected to swing once it has been lifted clear of the pins. If the load is especially heavy, large, and/or fragile, it could hurt workers and/or damage itself and nearby objects. By indicating whether the load remains in contact with the pins when it has been lifted a fraction of the length of the pins, the crane-load contact sensor helps the crane operator determine whether it is safe to lift the load clear of the pins: If there is contact, then the load is resting against the sides of the pins and, hence, it may not be safe to lift; if contact is occasionally broken, then the load is probably not resting against the pins, so it should be safe to lift. It is assumed that the load and base, or at least the pins and the surfaces of the alignment holes in the load, are electrically conductive, so the instrument can use electrical contact to indicate mechanical contact. However, DC resistance cannot be used as an indicator of contact for the following reasons: The load and the base are both electrically grounded through cables (the load is grounded through the lifting cable of the crane) to prevent discharge of static electricity. In other words, the DC resistance between the load and the pins is always low, as though they were always in direct contact. Therefore, instead of DC resistance, the instrument utilizes the AC electrical impedance between the pins and the load. The signal frequency used in the measurement is high enough (.1 MHz) that the impedance contributed by the cables and the electrical ground network of the building in which the crane and the base are situated is significantly greater than the contact impedance between the pins and the load. The instrument includes a signal generator and voltage-measuring circuitry, and is connected to the load and the base as shown in Figure 2. The output of the signal generator (typically having amplitude of the order of a volt) is applied to the load via a 50-resistor, and the voltage between the load and the pins is measured. When the load and the pins are not in contact, the impedance between them is relatively high, causing the measured voltage to exceed a threshold value. When the load and the pins are in contact, the impedance between them falls to a much lower value, causing the voltage to fall below the threshold value. The voltage-measuring circuitry turns on a red light-emitting diode (LED) to indicate the lower-voltage/ contact condition. Whenever the contact has been broken and the non-contact/higher-voltage condition has lasted for more than 2 ms, the voltage-measuring circuitry indicates this condition by blinking a green LED.

Youngquist, Robert↗

An Analysis of Representative Heating Load Lines for Residential HSPF Ratings

This report describes an analysis to investigate representative heating loads for single-family detached homes using current EnergyPlus simulations (DOE 2014a). Hourly delivered load results are used to determine binned load lines using US Department of Energy (DOE) residential prototype building models (DOE 2014b) developed by Pacific Northwest National Laboratory (PNNL). The selected residential single-family prototype buildings are based on the 2006 International Energy Conservation Code (IECC 2006) in the DOE climate regions. The resulting load lines are compared with the American National Standards Institute (ANSI)/Air-Conditioning, Heating, and Refrigeration Institute (AHRI) Standard 210/240 (AHRI 2008) minimum and maximum design heating requirement (DHR) load lines of the heating seasonal performance factor (HSPF) ratings procedure for each region. The results indicate that a heating load line closer to the maximum DHR load line, and with a lower zero load ambient temperature, is more representative of heating loads predicted for EnergyPlus prototype residential buildings than the minimum DHR load line presently used to determine HSPF ratings. An alternative heating load line equation was developed and compared to binned load lines obtained from the EnergyPlus simulation results. The effect on HSPF of the alternative heating load line was evaluated for single-speed and two-capacity heat pumps, and an average HSPF reduction of 16% was found. The alternative heating load line relationship is tied to the rated cooling capacity of the heat pump based on EnergyPlus autosizing, which is more representative of the house load characteristics than the rated heating capacity. The alternative heating load line equation was found to be independent of climate for the six DOE climate regions investigated, provided an adjustable zero load ambient temperature is used. For Region IV, the default DOE climate region used for HSPF ratings, the higher load line results in an ~28% increase in delivered heating load and an ~52% increase in the estimated heating operating cost over that given in the AHRI directory (AHRI 2014).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

IM3 + EPRI Data Center Load Projections

This dataset contains scenarios of hourly total electricity demand with and without projected loads from data centers over the period 2022-2040. The root projections without data center demands are identical to those documented in Burleyson et al. 2024. In short, those projections encompass hourly electricity demands for 54 Balancing Authorities (BAs) in the United States across a range of eight of weather and socioeconomic scenarios. Refer to the root dataset and accompanying publication, Burleyson et al. 2025, for information about how those projections were generated. For this derivative dataset we used the base loads from the following scenarios: rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 The root load projections did not reflect the drastic expansion of data centers that has occurred in the last several years to support artificial intelligence and cloud computing. To reflect growth in data center demand, a second set of load projections were created in which we layered in additional data center load projections based on the data center load growth scenarios described in a 2024 report by the Electric Power Research Institute (EPRI): "Powering Intelligence: Analyzing Artificial Intelligence and Data Center Energy Consumption". The EPRI projections from the report are included in this dataset (EPRI_2024_Projections.xlsx). That report contained annual state-level data center load projections for four year-over-year growth rates for data center demands: Low (3.71% annual growth) Moderate (5% annual growth) High (10% annual growth) Higher (15% annual growth) To homogenize the load projections with and without data centers we had to get them to a common scale. The first step was to take the EPRI annual state-level data center energy consumption values and convert them to 8760-hr loads for each year. We did that by assuming a flat (e.g., not weather- or time-sensitive) load profile and distributing the data center loads in each state evenly across all hours in a year. From there the loads were downscaled from the state-level to the county-level using 2019 county-level populations as weights. Finally, the county-level hourly data center loads were summed to the BA-level using the county-to-BA mapping underpinning the root load projections. The net result is 16 (4 weather and socioeconomic scenarios crossed with 4 data center load growth scenarios) unique load projections for the period 2022-2040. The file format follows that of the root dataset with a single additional column "Scaled_TELL_BA_Load_with_DC_MWh" that contains the hourly loads with the added data center loads for a given BA-year-scenario combination. Please refer to the readme file in the root dataset for more information on the file format.

Burleyson, Casey [Pacific Northwest National Labor↗

Strain Gage Load Calibration of the Wing Interface Fittings for the Adaptive Compliant Trailing Edge Flap Flight Test

The safety-of-flight parameters for the Adaptive Compliant Trailing Edge (ACTE) flap experiment require that flap-to-wing interface loads be sensed and monitored in real time to ensure that the structural load limits of the wing are not exceeded. This paper discusses the strain gage load calibration testing and load equation derivation methodology for the ACTE interface fittings. Both the left and right wing flap interfaces were monitored; each contained four uniquely designed and instrumented flap interface fittings. The interface hardware design and instrumentation layout are discussed. Twenty-one applied test load cases were developed using the predicted in-flight loads. Pre-test predictions of strain gage responses were produced using finite element method models of the interface fittings. Predicted and measured test strains are presented. A load testing rig and three hydraulic jacks were used to apply combinations of shear, bending, and axial loads to the interface fittings. Hardware deflections under load were measured using photogrammetry and transducers. Due to deflections in the interface fitting hardware and test rig, finite element model techniques were used to calculate the reaction loads throughout the applied load range, taking into account the elastically-deformed geometry. The primary load equations were selected based on multiple calibration metrics. An independent set of validation cases was used to validate each derived equation. The 2-sigma residual errors for the shear loads were less than eight percent of the full-scale calibration load; the 2-sigma residual errors for the bending moment loads were less than three percent of the full-scale calibration load. The derived load equations for shear, bending, and axial loads are presented, with the calculated errors for both the calibration cases and the independent validation load cases.

Miller, Eric J.↗

A Data-Driven Pivot-Point-Based Time-Series Feeder Load Disaggregation Method

The load profile at a feeder-head is usually known to utility engineers while the nodal load profiles are not. However, the nodal load profiles are increasingly important for conducting time-series analysis in distribution systems. Therefore, in this paper, we present a pivot-point based, two-stage feeder load disaggregation algorithm using smart meter data. The two stages are load profile selection (LPS) and load profile allocation (LPA). In the LPS stage, a random load profile selection process is first executed to meet the load diversity requirement. Then, a few pairs of pivot points are selected as the matching targets. After that, a matching algorithm will run repetitively to select one load profile at a time for matching the reference load profile at the pivot points. In the LPA stage, the LPS selected load profiles are allocated to each load node on the feeder considering distribution transformer loading limits, load composition, and square-footage. The proposed method is validated using actual data collected in a North Carolina service area. Finally, simulation results show that the proposed method can generate a unique load shape for each load node while match the shape of their aggregated profile with the actual feeder head load profile.

42 ENGINEERING↗