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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Prostate Bed Delineation Guidelines for Postoperative Radiation Therapy: On Behalf Of The Francophone Group of Urological Radiation Therapy

Prostate bed (PB) irradiation is considered the standard postoperative treatment after radical prostatectomy (RP) for tumors with high-risk features or persistent prostate-specific antigen, or for salvage treatment in case of biological relapse. Four consensus guidelines have been published to standardize practices and reduce the interobserver variability in PB delineation but with discordant recommendations. To improve the reproducibility in the PB delineation, the Francophone Group of Urological Radiotherapy (Groupe Francophone de Radiothérapie Urologique [GFRU]) worked to propose a new and more reproducible consensus guideline for PB clinical target volume (CTV) definition.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Using Temporal Deep Learning Models to Estimate Daily Snow Water Equivalent Over the Rocky Mountains

Abstract In this study we construct and compare three different deep learning (DL) models for estimating daily snow water equivalent (SWE) from high‐resolution gridded meteorological fields over the Rocky Mountain region. To train the DL models, Snow Telemetry (SNOTEL) station‐based SWE observations are used as the prediction target. All DL models produce higher median Nash‐Sutcliffe Efficiency (NSE) values than a conceptual SWE model and interpolated gridded data sets, although mean squared errors also tend to be higher. Sensitivity of the SWE prediction to the model's input variables is analyzed using an explainable artificial intelligence (XAI) method, yielding insight into the physical relationships learned by the models. This method reveals the dominant role precipitation and temperature play in snowpack dynamics. In applying our models to estimate SWE throughout the Rocky Mountains, an extrapolation problem arises since the statistical properties of SWE (e.g., annual maximum) and geographical properties of individual grid points (e.g., elevation) differ from the training data. This problem is solved by normalizing the SWE with its historical maximum value to alleviate extrapolation for all tested DL models. Our work shows that the DL models are promising tools for estimating SWE, and sufficiently capture relevant physical relationships to make them useful for spatial and temporal extrapolation of SWE values.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The effect of dust bias on the census of neutral gas and metals in the high-redshift Universe due to SDSS-II quasar colour selection

ABSTRACT We present a systematic study of the impact of a dust bias on samples of damped Ly α absorbers (DLAs). This bias arises as an effect of the magnitude and colour criteria utilized in the Sloan Digital Sky Survey (SDSS) quasar target selection up until data release 7 (DR7). The bias has previously been quantified assuming only a contribution from the dust obscuration. In this work, we apply the full set of magnitude and colour criteria used up until SDSS-DR7 in order to quantify the full impact of dust biasing against dusty and metal-rich DLAs. We apply the quasar target selection algorithm on a modelled population of intrinsic colours, and by exploring the parameter space consisting of redshift, ($z_{\rm{\small QSO}}$and zabs), optical extinction, and H i column density, we demonstrate how the selection probability depends on these variables. We quantify the dust bias on the following properties derived for DLAs at z ≈ 3: the incidence rate, the mass density of neutral hydrogen and metals, and the average metallicity. We find that all quantities are significantly affected. When considering all uncertainties, the mass density of neutral hydrogen is underestimated by 10–50 per cent, and the mass density in metals is underestimated by 30–200 per cent. Lastly, we find that the bias depends on redshift. At redshift z = 2.2, the mass density of neutral hydrogen and metals might be underestimated by up to a factor of 2 and 5, respectively. Characterizing such a bias is crucial in order to accurately interpret and model the properties and metallicity evolution of absorption-selected galaxies.

Krogager, Jens-Kristian↗
DOE OSTI2016

SPRUCE Deep Peat Heating (DPH) Peat Water Content and Temperature for Experimental Plot Cores, June 2014 through June 2015

This data set provides the peat water content and peat temperature at time of sampling for peat cores collected before and during the SPRUCE Deep Peat Heating (DPH) study. Cores were collected during three sampling events: 03 June 2014, 09 September 2014, and 16 June 2015. Two cores were extracted from hollow locations in each of the 10 experimental plots (4, 6, 8, 10, 11, 13, 16, 17, 19, and 20). The five ambient plots (5, 7, 14, and 21) were not included in the DPH sampling efforts. See Table 1. Cores were partitioned into samples at 11 depth increments: 0-10, 10-20, 20-30, 30-40, 40-50, 50-75, 75-100, 100-125, 125-150, 150-175, and 175-200 cm below surface of the hollow. The DPH study was undertaken to evaluate possible rapid responses of deep peat carbon (C) stocks, microbial communities, and biogeochemical cycling processes to unprecedented temperatures. In June 2014, deep soil heating was initiated at 5 warming levels (+0, +2.25, +4.5, +6.75 and +9 °C) with 2 replicate plots per level. Warming levels at depth were achieved over a 25 (+ 2.25 °C) to 60-day (+9 °C) period depending on the target treatment temperatures. Data file – There is one comma-separated (*.csv) file with peat core water content and temperature at time of sampling, plus the amount of dried archived material retained after analyses. User Note: In this third release, four variables related to extrapolations of peat core temperature were removed. See the Data Set History table for additional details. 25-150, 150-175, and 175-200 cm below surface of the hollow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Mixed-Phase Cloud Base Ice Precipitation Properties During the M-PACE Field Campaign

Cloud-climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long-lived, and nearly-continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud-base properties a more appealing target for inference and evaluation of model simulations. This dataset provides a set of 25 samples from the M-PACE field campaign, all of which were retrieved using the synthesis of ARM radar and lidar measurements. The retrieved ice precipitation variables in this dataset include, among others, the ice number concentration, water content, PSD parameters, precipitation rate, mass-weighted fall velocity, vertical air motion, and effective radius, all of which are highly valuable for model evaluation and a general understanding of polar cloud sink processes. Each variable sample includes its mean value and associated uncertainty. Additional variables based on ARM measurements (liquid layer statistics, etc.) are included in this dataset as well. The retrieval algorithm and analysis of this dataset are described in Silber (JGR, 2023, https://doi.org/10.1029/2022JD038202).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Propagation of high-energy laser beams through the earth's atmosphere II; Proceedings of the Meeting, Los Angeles, CA, Jan. 21-23, 1991

Consideration is given to turbulence at the inner scale, modeling turbulent transport in laser beam propagation, variable wind direction effects on thermal blooming correction, realistic wind effects on turbulence and thermal blooming compensation, wide bandwidth spectral measurements of atmospheric tilt turbulence, remote alignment of adaptive optical systems with far-field optimization, focusing infrared laser beams on targets in space without using adaptive optics, and a simplex optimization method for adaptive optics system alignment. Consideration is also given to ground-to-space multiline propagation at 1.3 micron, a path integral approach to thermal blooming, functional reconstruction predictions of uplink whole beam Strehl ratios in the presence of thermal blooming, and stability analysis of semidiscrete schemes for thermal blooming computation.

Ulrich, Peter B.↗
NASA NTRS2018

Management of Leshmaniases in the Era of Climate Change in Morocco

The proliferation of vector-borne diseases are predicted to increase in a changing climate and Leishmaniases, as a vector-borne diseases, are re-emerging diseases in several regions of the world. In Morocco, during the last decade, a sharp increase in cutaneous leishmaniases cases has been reported. Nevertheless, in Morocco, leishmaniases are a major public health problem, and little interest was given to climate change impacts on the distribution and spread of these diseases. As insect-borne diseases, the incidence and distribution of leishmaniases are influenced by environmental changes, but also by several socio-economic and cultural factors. From a biological point of view, environmental variables have effects on the survival of insect vectors and mammalian reservoirs, which, in turn, affects transmission. Here, we highlight the effects of climate change in Morocco and discuss its consequences on the epidemiology of leishmaniases to identify challenges and define targeted recommendations to fight this disease.

climate change↗
NASA NTRSDate not supplied

Mapping Surface Vapor Pressure Deficits From Geostationary Satellites for Fire Weather Monitoring

The increase in the wildfires were observed globally in accordance with global warming, and to real- time monitoring of wildfire risk in broad scale is demanded for wildfire management to prevent the spread of wildfires. Scientists invented a lot of indices to assess the wildfire risk. Vapor Pressure Deficit (VPD) is one of the most important meteorological components for those indices. Compared to other components of fire weather indices, VPD can change quickly from lower risk to higher risk even in sub-hourly. Therefore, real-time fire risk monitoring requires high-resolution and high- temporal VPD spatial map. Here, we developed VPD estimation method using the GOES Advanced Baseline Imager (ABI) data. Unlike the polar-orbital satellite data, the ABI can observe target region every 10 minutes, so that we can estimate VPD for fire weather in real-time. The method used to estimate VPD is same with the algorithm of NASA Earth Exchange Gridded Daily Meteorology (NEX- GDM), which estimate meteorological variables from ground weather observation and spatial variables based on random forest (RF). We calculated RF importance to select bands of ABI as input of the model. To validate our results, we compared the spatial pattern of our VPD data with the Real- Time Mesoscale Analysis (RTMA) data over the conterminous USA. We sought possibility of applying our method to the region where no real-time high-resolution weather data is available, such as South America. The developed method can produce real-time high-resolution high-frequent VPD data in the continental scale. The derived data from GOES ABI could contribute to improve the fire weather monitoring and lead to prevent wildfires.

Hirofumi Hashimoto↗
NASA NTRS2006

Magnetite in Martian Meteorite Mil 03346 and Gusev Adirondack Class Basalt: Moessbauer Evidence for Variability in the Oxidation State of Adirondack Lavas

The Moessbauer spectrometers on the Mars Exploration Rovers Spirit (Gusev crater) and Opportunity (Meridiani Planum) have returned information on the oxidation state of iron, the mineralogical composition of Fe-bearing phases, and the distribution of Fe among oxidation states and phases [1,2,3]. To date, ~100 and ~85 surface targets have been analyzed by the Spirit and Opportunity spectrometers, respectively. Twelve component subspectra (8 doublets and 4 sextets) have been identified and most have been assigned to mineralogical compositions [4]. Two sextet subspectra result from the opaque and strongly magnetic mineral magnetite (Fe3O4 for the stoichiometric composition), one each for the crystallographic sites occupied by tetrahedrally-coordinated Fe3+ and by octahedrally-coordinated Fe3+ and Fe2+. At Gusev crater, the percentage of total Fe associated with magnetite for rocks ranges from 0 to ~ 35% (Fig. 1) [3]. The range for soils (~5 to ~12% of total Fe from Mt, with one exception) is narrower. The ubiquitous presence of Mt in soil firmly establishes the phase as the strongly magnetic component in martian soil

Morris, R. V.↗
NASA NTRS2006

Magnetite in Martian Meteorite Mil 03346 and Gusev Adirondack Class Basalt: Mossbauer Evidence for Variability in the Oxidation State of Adirondack Lavas

The Moessbauer spectrometers on the Mars Exploration Rovers Spirit (Gusev crater) and Opportunity (Meridiani Planum) have returned information on the oxidation state of iron, the mineralogical composition of Fe-bearing phases, and the distribution of Fe among oxidation states and phases [1,2,3]. To date, approx.100 and approx.85 surface targets have been analyzed by the Spirit and Opportunity spectrometers, respectively. Twelve component subspectra (8 doublets and 4 sextets) have been identified and most have been assigned to mineralogical compositions [4]. Two sextet subspectra result from the opaque and strongly magnetic mineral magnetite (Fe3O4 for the stoichiometric composition), one each for the crystallographic sites occupied by tetrahedrally-coordinated Fe3+ and by octahedrally-coordinated Fe3+ and Fe2+. At Gusev crater, the percentage of total Fe associated with magnetite for rocks ranges from 0 to approx. 35% (Fig. 1) [3]. The range for soils (approx.5 to approx.12% of total Fe from Mt, with one exception) is narrower. The ubiquitous presence of Mt in soil firmly establishes the phase as the strongly magnetic component in martian soil [4,5].

Morris, R. V.↗
DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗
DOE OSTI2012

THE A-X INFRARED BANDS OF ALUMINUM OXIDE IN STARS: SEARCH AND NEW DETECTIONS

We describe a search for the A-X infrared bands of AlO with a view toward better understanding the characteristics of this radical. These bands are infrequently encountered in astronomical sources but surprisingly were very prominent in the spectra of two well-known, novalike variables (V838 Mon and V4332 Sgr) thereby motivating us to explore the physical conditions necessary for their excitation. In this study, we present the detection of A-X bands in the spectra of 13 out of 17 stars, selected on the basis of their J - K colors as potential candidates for detection of these bands. The majority of the AlO detections are in asymptotic giant branch (AGB) stars, viz., nine OH/IR stars, two Mira variables, and two bright infrared sources. Our study shows that the A-X bands are fairly prevalent in sources with low temperature and O-rich environments. Interesting variation in the strength of the AlO bands in one of the sources (IRAS 18530+0817) is reported and the cause for this is examined. Possible applications of the present study are discussed in terms of the role of AlO in alumina dust formation, the scope for estimating the radioactive {sup 26}Al content in AGB stars from the A-X bands, and providing possible targets for further mm/radio studies of AlO which has recently been discovered at millimeter wavelengths.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Non-linear evolution in QCD at high-energy beyond leading order

The standard formulation of the high-energy evolution in perturbative QCD, based on the Balitsky-Kovchegov equation, is known to suffer from severe instabilities associated with radiative corrections enhanced by double transverse logarithms, which occur in all orders starting with the next-to-leading one. Over the last years, several methods have been devised to resum such corrections by enforcing the time-ordering of the successive gluon emissions. We observe that the instability problem is not fully cured by these methods: various prescriptions for performing the resummation lead to very different physical results and thus lack of predictive power. We argue that this problem can be avoided by using the rapidity of the dense target (which corresponds to Bjorken x) instead of that of the dilute projectile as an evolution time. This automatically ensures the proper time-ordering and also allows for a direct physical interpretation of the results. We explicitly perform this change of variables at NLO. We observe the emergence of a new class of double logarithmic corrections, potentially leading to instabilities, which are however less severe, since disfavoured by the typical BK evolution for “dilute-dense” scattering. We propose several prescriptions for resumming these new double-logarithms to all orders and find only little scheme dependence: different prescriptions lead to results which are consistent to each other to the accuracy of interest. We restore full NLO accuracy by completing one of the resummed equations (non-local in rapidity) with the remaining NLO corrections.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Agreement Among RTOG Sarcoma Radiation Oncologists in Contouring Suspicious Peritumoral Edema for Preoperative Radiation Therapy of Soft Tissue Sarcoma of the Extremity

Purpose: Peritumoral edema may harbor sarcoma cells. The extent of suspicious edema (SE) included in the treatment volume is subject to clinical judgment, balancing the risk of missing tumor cells with excess toxicity. Our goal was to determine variability in SE delineation by sarcoma radiation oncologists (RO). Methods and Materials: Twelve expert ROs were provided with T1 gadolinium and T2-weighted MR images of 10 patients with high-grade extremity soft-tissue sarcoma. Gross tumor volume, clinical target volume (CTV)3cm (3 cm longitudinal and 1.5 cm radial margin), and CTV2cm (2 cm longitudinal and 1 cm radial margin) were contoured by a single observer. Suspicious peritumoral edema, defined as abnormal signal on T2 images, was independently delineated by all 12 ROs. Contouring agreement was analyzed using the simultaneous truth and performance level estimation (STAPLE) algorithm and kappa statistics. Results: The mean volumes of GTV, CTV2cm, and CTV3cm were, respectively, 130 cm{sup 3} (7-413 cm{sup 3}), 280 cm{sup 3} and 360 cm{sup 3}. The mean consensus volume computed using the STAPLE algorithm at 95% confidence interval was 188 cm{sup 3} (24-565 cm{sup 3}) with a substantial overall agreement corrected for chance (mean kappa = 0.71; range: 0.32-0.87). The minimum, maximum, and mean volume of SE (excluding the GTV) were 4, 182, and 58 cm{sup 3} (representing a median of 29% of the GTV volume). The median volume of SE not included in the CTV2cm and in the CTV3cm was 5 and 0.3 cm{sup 3}, respectively. There were 3 large tumors with >30 cm{sup 3} of SE not included in the CTV3cm volume. Conclusion: Despite the fact that SE would empirically seem to be a more subjective volume, a substantial or near-perfect interobserver agreement was observed in SE delineation in most cases with high-grade soft-tissue sarcomas of the extremity. A median of 97% of the consensus SE is within the CTV2cm (99.8% within the CTV3cm). In a minority of cases, however, significant expansion of the CTVs is required to cover SE.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual quality assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges. Results: The observer study indicated that, for each image quality attribute, the averaged observer ranking strongly correlated with the algorithmic ranking (linear correlation coefficient R > 0.92), with highest correlation (R = 1) for lung gray level and the lowest (R = 0.92) for mediastinum noise. There was a strong concordance between the observers in terms of their rankings (i.e., Kendall’s tau agreement > 0.84). The observers also generally indicated similar tolerance and preference levels in terms of acceptable ranges, as 85% of the values were close to the overall tolerance or preference levels and the differences were smaller than 0.15. Conclusions: The observer study indicates that the previously proposed technique provides a robust reflection of the perceptual image quality in clinical images. The results established the range of algorithmic outputs for each metric that can be used to quantitatively assess and qualify the appearance quality of clinical chest radiographs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-T-232: Custom High-Dose-Rate Brachytherapy Surface Mold Applicators: The Importance Source to Skin Distance

Purpose: Surface mold applicators can be customized to fit irregular skin surfaces that are difficult to treat with other radiation therapy techniques. Optimal design of customized HDR skin brachytherapy is not well-established. We evaluated the impact of applicator thickness (source to skin distance) on target dosimetry. Methods: 27 patients had 34 treated sites: scalp 4, face 13, extremity 13, and torso 4. Custom applicators were constructed from 5–15 mm thick thermoplastic bolus molded over the skin lesion. A planar array of plastic brachytherapy catheters spaced 5–10 mm apart was affixed to the bolus. CT simulation was used to contour the target volume and to determine the prescription depth. Inverse planning simulated annealing followed by graphical optimization was used to plan and deliver 40–56 Gy in 8–16 fractions. Target coverage parameters (D90, Dmean, and V100) and dose uniformity (V110–200, D0.1cc, D1cc, and D2cc) were studied according to target depth (<5mm vs. ≥5mm) and applicator thickness (5–10mm vs. ≥10mm). Results: The average prescription depth was 4.2±1.5mm. The average bolus thickness was 9.2±2.4mm. The median CTV volume was 10.0 cc (0.2–212.4 cc). Similar target coverage was achieved with prescription depths of <5mm and ≥5mm (Dmean = 113.8% vs. 112.4% and D90 = 100.2% vs. 98.3%). The <5mm prescription depth plans were more uniform (D0.1cc = 131.8% vs. 151.8%). Bolus thickness <10mm vs. ≥10mm plans also had similar target coverage (Dmean = 118.2% vs. 110.7% and D90 = 100.1% vs. 99.0%). Applicators ≥10mm thick, however, provide more uniform target dosimetry (D0.1cc = 146.9% vs. 139.5%). Conclusion: Prescription depth is based upon the thickness of the lesion and upon the clinical needs of the patient. Applicators ≥10mm thick provide more dose uniformity than 5–10mm thick applicators. Applicator thickness is an important variable that should be considered during treatment planning to achieve optimal dose uniformity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Properties of amorphous carbon thin films grown by ion beam sputtering

The electrical performance of amorphous carbon thin films obtained by the ion beam sputtering of a carbon target in argon has been investigated. It has been shown by the Raman spectroscopy method that these films have a graphite-like structure. It has also been found by conductivity and thermopower studies that the hopping mechanism of conductivity with a variable length of hops over localized states near the Fermi level changes to the mechanism of hopping over the nearest neighbors as the temperature rises from 77 to 190 K. Near room temperature, electrotransport is provided by variable-length hops over localized states at the tail of the valence band.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

On the Path to SunShot. Advancing Concentrating Solar Power Technology, Performance, and Dispatchability

This report examines the remaining challenges to achieving the competitive concentrating solar power (CSP) costs and large-scale deployment envisioned under the U.S. Department of Energy's SunShot Initiative. Although CSP costs continue to decline toward SunShot targets, CSP acceptance and deployment have been hindered by inexpensive photovoltaics (PV). However, a recent analysis found that thermal energy storage (TES) could increase CSP's value--based on combined operational and capacity benefits--by up to 6 cents/kWh compared to variable-generation PV, under a 40% renewable portfolio standard in California. Thus, the high grid value of CSP-TES must be considered when evaluating renewable energy options. An assessment of net system cost accounts for the difference between the costs of adding new generation and the avoided cost from displacing other resources providing the same level of energy and reliability. The net system costs of several CSP configurations are compared with the net system costs of conventional natural-gas-fired combustion-turbine (CT) and combined-cycle plants. At today's low natural gas prices and carbon emission costs, the economics suggest a peaking configuration for CSP. However, with high natural gas prices and emission costs, each of the CSP configurations compares favorably against the conventional alternatives, and systems with intermediate to high capacity factors become the preferred alternatives. Another analysis compares net system costs for three configurations of CSP versus PV with batteries and PV with CTs. Under current technology costs, the least-expensive option is a combination of PV and CTs. However, under future cost assumptions, the optimal configuration of CSP becomes the most cost-effective option.

14 SOLAR ENERGY↗