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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
DOE OSTI2023

Search for resonances in events with photon and jet final states in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for resonances in events with the γ+jet final state has been performed using proton-proton collision data collected at $\sqrt s$ = 13 TeV by the CMS experiment at the LHC. The total data analyzed correspond to an integrated luminosity of 138 fb –1 . Models of excited quarks and quantum black holes are considered. Using a wide-jet reconstruction for the candidate jet, the γ+jet invariant mass spectrum measured in data is examined for the presence of resonances over the standard model continuum background. The background is estimated by fitting this mass distribution with a functional form. The data exhibit no statistically significant deviations from the expected standard model background. Exclusion limits at 95% confidence level on the resonance mass and other parameters are set. Excited light-flavor quarks (excited bottom quarks) are excluded up to a mass of 6.0 (3.8) TeV. Quantum black hole production is excluded for masses up to 7.5 (5.2) TeV in the Arkani-Hamed-Dimopoulos-Dvali (Randall-Sundrum) model. These lower mass bounds are the most stringent to date among those obtained in the γ+jet final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Generalized parton distributions and gravitational form factors at large momentum transfer

Within the soft collinear effective theory (SCET), we derive a factorization theorem which resums Sudakov logarithms (α s ln 2 ( –t)) n to all orders in the quark-in-quark generalized parton distribution (GPD) at large momentum transfer t, and perform a consistency check to one-loop. We show that the same Sudakov factor appears in the ‘Feynman’ contribution to the GPDs of the nucleon. Our result enables the resummation of all the large logarithms ln Q 2 and ln 2 t in exclusive processes with two hard scales Λ$^{2}_{QCD}$ ≪ |t| ≪ Q 2 . We also present a SCET power counting analysis of the Feynman contributions to the GPDs and show that the x-dependence of GPDs factorizes at large-t with controlled corrections. This in particular implies that any ratio of GPD moments such as the electromagnetic and gravitational form factors (GFF) is perturbatively calculable in this approximation. Furthermore, we identify a novel order α s power-law t-dependence in the GPD and the D-type GFF that will dominate over the standard order α$^{2}_{s}$ ‘leading twist’ asymptotic contribution in the phenomenologically relevant region of t.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Spinor representations for fields with any spin: Lorentz tensor basis for operators and covariant multipole decomposition

This paper discusses a framework to parametrize and decompose operator matrix elements for particles with higher spin (j > 1/2) using chiral representations of the Lorentz group, i.e. the (j, 0) and (0, j) representations and their parity-invariant direct sum. Unlike traditional approaches that require imposing constraints to eliminate spurious degrees of freedom, these chiral representations contain exactly the 2j + 1 components needed to describe a spin-j particle. The central objects in the construction are the t-tensors, which are generalizations of the Pauli four-vector σ μ for higher spin. For the generalized spinors of these representations, we demonstrate how the algebra of the t-tensors allows to formulate a generalization of the Dirac matrix basis for any spin. For on-shell bilinears, we show that a set consisting exclusively of covariant multipoles of order 0 ≤ m ≤ 2j forms a complete basis. We provide explicit expressions for all bilinears of the generalized Dirac matrix basis, which are valid for any spin value. As a byproduct of our derivations we present an efficient algorithm to compute the t-tensor matrix elements. The formalism presented here paves the way to use a more unified approach to analyze the non-perturbative QCD structure of hadrons and nuclei across different spin values, with clear physical interpretation of the resulting distributions as covariant multipoles.

Angular momentum of light↗
DOE OSTI2025

Search for resonant leptoquark production via lepton-jet signatures in pp collisions at $\sqrt{s}=13$ TeV and $\sqrt{s}=13.6$ TeV with the ATLAS detector

This paper presents a search for physics beyond the Standard Model targeting a heavy resonance visible in the invariant mass of the lepton-jet system. The analysis focuses on final states with a high-energy lepton and jet, and is optimised for the resonant production of leptoquarks — a novel production mode mediated by the lepton content of the proton originating from quantum fluctuations. Four distinct and orthogonal final states are considered: e+light jet, μ+light jet, e+b-jet, and μ+b-jet, constituting the first search at the Large Hadron Collider for resonantly produced leptoquarks with couplings to electrons and muons. Events with an additional same-flavour lepton, as expected from higher-order diagrams in the signal process, are also included in each channel. The search uses proton-proton collision data from the full Run 2, corresponding to an integrated luminosity of 140 fb −1 at a centre-of-mass energy of $\sqrt{s}=13$ TeV, and from a part of Run 3 (2022–2023), corresponding to 55 fb −1 at $\sqrt{s}=13.6$ TeV. No significant excess over Standard Model predictions is observed. The results are interpreted as exclusion limits on scalar leptoquark ($\tilde{S}$ 1 ) production, substantially improving upon previous ATLAS constraints from leptoquark pair production for large coupling values. The excluded $\tilde{S}$ 1 $\tilde{S}$ 1 mass ranges depend on the coupling strength, reaching up to 3.4 TeV for quark-lepton couplings y de = 1.0, and up to 4.3 TeV, 3.1 TeV, and 2.8 TeV for y sμ , y be , and y bμ couplings set to 3.5, respectively.

Hadron-Hadron Scattering↗
DOE OSTI2026

The Spatial and Temporal Variability of the Clear Convective Boundary Layer at the ARM SGP Supersite

The convective boundary layer (CBL), also known as the mixing layer, constitutes the critical lower segment of the atmosphere that significantly influences daily human activities. The growing demand for precise weather forecasts is driven by the requirements of agriculture, transportation, and routine societal functions. Here, to enhance understanding of the CBL, this study investigates the spatiotemporal variability in the CBL and its controlling factors using four-year Doppler lidar, surface flux, and profiling measurements at five ARM Southern Great Plains sites within a 100 km radius. This investigation utilizes data collected exclusively under clear-sky conditions or scattered low-cloud conditions. Results reveal significant spatial differences in CBL evolutions. Daily mixing layer heights (MLHs) vary up to 1 km (30% of the mean) in late afternoon. There is a clear east–west contrast: western sites (C1, E32, E37) exhibit higher summer MLH (1.9–2.1 km) and vertical velocity variances (1.0–1.2 m 2 s −2 ) than eastern sites (1.6–1.8 km), reversing in winter. Temporally, the MLH peaks at 70% of the sunrise–sunset interval, the lagging heat flux (HF) peaks at 50%; and the seasonal MLH maxima lag the HF by approximately one month, influenced by nighttime PBL (planetary boundary layer) properties. The HF and lower tropospheric stability are the main factors of influence for the CBL, but site-specific dependencies highlight the critical roles of local factors, underscoring the need for including them in CBL modeling.

ARM SGP site↗
DOE OSTI2026

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strong QCD Insights from Excited Nucleon Structure Studies with CLAS and CLAS12

Studies of the spectrum of hadrons and their structure in experiments with electromagnetic probes offer unique insight into many facets of the strong interaction in the regime of large quark-gluon running coupling, i.e. the regime of strong QCD. The experimental program within Hall B at Jefferson Laboratory based on data acquired with the CLAS spectrometer using electron and photon beams with energies up to 6 GeV has already considerably extended the scope of research in hadron physics in joint efforts between experiment and phenomenological data analysis. Impressive progress in relating the hadron structure observables inferred from the data to the strong QCD mechanisms underlying hadron mass generation has been achieved in the past decade. Furthermore, these results will be considerably extended with data from the experimental program with the new CLAS12 spectrometer that has begun data taking using electron beams with energies up to 11 GeV. With this extended kinematic reach the structure of nucleon resonances will be probed at the highest photon virtualities ever achieved in the studies of exclusive electroproduction, which will allow for the exploration of the distance scale where>98% of light hadron mass emerges from QCD in the transition of the strong interaction from the regime of quark-gluon confinement to perturbative QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Polarized Proton Structure in the Resonance Region

In view of the precise data available on inclusive polarized electron scattering off polarized proton targets in the nucleon resonance excitation region, we compare these results with the coherent sum of resonant contributions to the polarized structure function g 1 and virtual photon asymmetry A 1 . To this goal, we employ the nucleon resonance electroexcitation amplitudes determined for photon virtualities Q 2 < 5.0 GeV 2 from analyses of the CLAS data on exclusive electroproduction off protons in the resonance region. Most of the well established resonances of four star PDG status in the mass range up to 1.75 GeV are included. We find that the resonance-like structures observed in the inclusive g 1 data are related to the resonant contributions in the entire range of photon virtuality Q 2 where the data on g 1 are available. In the range of invariant mass of the final hadron system W > 1.5 GeV, the data on the asymmetry A 1 are well reproduced even when accounting for resonant contributions only, especially for the larger values of Q 2 and energies analysed. This observation offers an interesting hint to quark-hadron duality seen in polarized inclusive electron scattering observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Soil Particulate Organic Matter is Related to Ericoid Mycorrhizal Shrubs, not Ectomycorrhizal Trees, in a Temperate Forest

Mycorrhizal associations are key drivers of soil biogeochemistry, but previous studies have focused almost exclusively on ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) associations. Ericoid mycorrhizal (ErM) shrubs frequently occur in forest understories and are expanding in response to disturbance, but are rarely considered in biogeochemical frameworks. We investigated the relationships of understory ErM shrubs and overstory trees on carbon (C) and nitrogen (N) in soil organic matter fractions in a southern Appalachian temperate forest. We sampled the 0–10 cm mineral soil layer from 43 plots at the Coweeta Hydrologic Laboratory, across gradients in overstory EcM dominance and understory ErM shrub biomass. Soil C:N ratios increased with both increasing EcM dominance and increasing ErM shrub biomass. However, total particulate organic matter (POM) C, and the proportion of C and N held in POM increased with increasing ErM shrub biomass, but not with increasing EcM dominance. In contrast, mineral-associated organic matter (MAOM) C and N were negatively associated with EcM dominance, but were not related to ErM shrubs. Our findings suggest that ErM shrubs facilitate POM formation while AM trees promote MAOM formation. Because ErM shrub biomass represents a small fraction of total forest biomass, our work provides evidence that ErM shrubs have an outsized effect on soil organic matter, which advocates for their inclusion in mechanistic studies and biogeochemical frameworks.

Bonilla, Kayla A. [University of Georgia, Athens, ↗
DOE OSTI2020

Dynamics and drivers of land use and land cover changes in Bangladesh

Abstract Bangladesh has undergone dramatic land use and land cover changes (LULCC) in recent years, but no quantitative analysis of LULCC drivers at the national scale exists so far. Here, we quantified the drivers of major LULCC in combination with biophysical and socioeconomic observations at the sub-district level. We used Landsat satellite data to interpret LULCC from 2000 to 2010 and employed a Global Surface Water Dataset to account for the influences of water seasonality. The results suggest that major LULCC in Bangladesh occur between agricultural land and waterbodies and between forest and shrubland. Exclusion of seasonal waterbodies can improve the accuracy of our LULCC results and driver analysis. Although the gross gain and loss of agricultural land are large on the local scale, the net change (gross gain minus gross loss) at a country scale is almost negligible. Climate dynamics and extreme events and changes in urban and rural households were driving the changes from forest to shrubland in the southeast region. The conversion from agricultural land to standing waterbodies in the southwest region was mainly driven by urban household dynamics, population growth, distance to cities and major roads, and precipitation dynamics. This study, which is the first effort accounting for water seasonality and quantifying biophysical and socioeconomic drivers of LULCC at the national scale, provides a perspective on overall LULCC and underlying drivers over a decadal time scale and national spatial scale and can serve as a scientific basis for developing land policies in Bangladesh.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Rainfall events stimulate episodic associative nitrogen fixation in switchgrass

Abstract Associative N 2 fixation (ANF) is widespread but poorly characterized, limiting our ability to estimate global inputs from N 2 fixation. In some places, ANF rates are at or below detection most of the time but occasionally and unpredictably spiking to very high rates. Here we test the hypothesis that plant phenology and rainfall events stimulate ANF episodes. We measured ANF in intact soil cores in switchgrass ( Panicum virgatum L.) in Michigan, USA. We used rain exclusion shelters to impose three rainfall treatments with each receiving 60 mm of water over a 20-day period but at different frequencies. We concurrently established a treatment that received ambient rainfall, and all four treatments were replicated four times. To assess the effects of plant phenology, we measured ANF at key phenological stages in the ambient treatment. To assess the effects of rainfall, we measured ANF immediately before and immediately after each wetting event in each treatment involving rainfall manipulation. We found that the previous day’s rainfall could explain 29% of the variation in ANF rates within the ambient treatment alone, and that bulk soil C:N ratio was also positively correlated with ANF, explaining 18% of the variation alone. Wetting events increased ANF and the magnitude of response to wetting increased with the amount of water added and decreased with the amount of inorganic N added in water. ANF episodes thus appear to be driven primarily by wetting events. Wetting events likely increase C availability, promote microbial growth, and make rhizosphere conditions conducive to ANF.

Vizza, Carmella (ORCID:0000000292690357)↗
DOE OSTI2020

A model for discrete fracture-clay rock interaction incorporating electrostatic effects on transport

Abstract A model based on the code CrunchClay is presented for a fracture-clay matrix system that takes electrostatic effects on transport into account. The electrostatic effects on transport include those associated with the development of a diffusion potential as captured by the Nernst-Planck equation, and the formation of a diffuse layer bordering negatively charged clay particles within which partial anion exclusion occurs. The model is based on a dual continuum formulation that accounts for diffuse layer and bulk water pore space, providing a more flexible framework than is found in the classical mean electrostatic potential models. The diffuse layer model is obtained by volume averaging ion concentrations in the Poisson-Boltzmann equation, but also includes the treatment of longitudinal transport within this continuum. The calculation of transport within the bulk and diffuse layer porosity is based on a new formulation for the Nernst-Planck equation that considers averaging of diffusion coefficients and accumulation factors at grid cell interfaces. Equations for function residuals and the associated Jacobian matrix are presented such that the system of nonlinear differential-algebraic equations can be solved with Newton’s method. As an example, we consider a 2D system with a single discrete fracture within which flow and advective transport occurs that is coupled to diffusion in the clay-rich matrix. The simulation results demonstrate the lack of retardation for anions (e.g., 36 Cl − ) of the contaminant plume within the fracture flow system because they are largely excluded from the charged clay rock, while the migration of cations (e.g., 90 Sr ++ ) is more strongly attenuated. The diffusive loss of divalent cations in particular from the fracture is accentuated by their accumulation in the diffuse layer within the clay-rich matrix.

58 GEOSCIENCES↗
DOE OSTI2025

Metabolic skinflint or spendthrift? Insights into ground sloth integument and thermophysiology revealed by biophysical modeling and clumped isotope paleothermometry

Abstract Remains of megatheres have been known since the 18th -century and were among the first megafaunal vertebrates to be studied. While several examples of preserved integument show a thick coverage of fur for smaller ground sloths living in cold climates such as Mylodon and Nothrotheriops , comparatively very little is known about megathere skin. Assuming a typical placental mammal metabolism, it was previously hypothesized that megatheres would have had little-to-no fur as they achieved giant body sizes. Here the “hairless model of integument” is tested using geochemical analyses to estimate body temperature to generate novel models of ground sloth metabolism, fur coverage, and paleoclimate with Niche Mapper software. The simulations assuming metabolic activity akin to those of modern xenarthrans suggest that sparse fur coverage would have resulted in cold stress across most latitudinal ranges inhabited by extinct ground sloths. Specifically, Eremotherium predominantly required dense 10 mm fur with implications for seasonal changes of coat depth in northernmost latitudes and sparse fur in the tropics; Megatherium required dense 30 mm fur year-round in its exclusive range of cooler, drier climates; Mylodon and Nothrotheriops required dense 10–50 mm fur to avoid thermal stress, matching the integument remains of both genera, and further implying the use of behavioral thermoregulation. Moreover, clumped isotope paleothermometry data from the preserved teeth of four genera of ground sloth yielded reconstructed body temperatures lower than those previously reported for large terrestrial mammals (29 ± 2°–32 ± 3° C). This combination of low metabolisms and thick fur allowed ground sloths to inhabit various environments.

Deak, Michael D.↗
DOE OSTI2026

Entropy Stable Conservative Flux Form Neural Networks

We propose an entropy-stable conservative flux form neural network (CFN) to predict the dynamics of unknown governing conservation laws. The design of the network is based on the entropy-stable, second-order, and non-oscillatory Kurganov-Tadmor (KT) scheme. The proposed entropy-stable CFN, hereafter referred to as ESCFN, uses slope limiting as a denoising mechanism, ensuring accurate predictions in both noisy and sparse observation environments, as well as in both smooth and discontinuous regions. Importantly, our method is designed to predict long term dynamics of the unknown conservation law exclusively from a short temporal window of observed data, that is, without oracle knowledge of the PDE or later-time solution profiles. Numerical experiments demonstrate that the ESCFN achieves both stability and conservation while maintaining accuracy over extended time domains, and successfully predicts shock propagation speeds in long-term simulations. Furthermore, it is also robust to both noisy and sparse data environments.

Hyperbolic conservation laws↗
DOE OSTI2022

The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction

Abstract Context Habitat fragmentation is a leading threat to biodiversity, yet the impacts of fragmentation on most taxa, let alone interactions among those taxa, remain largely unknown. Objectives We studied how three consequences of fragmentation—reduced patch connectivity, altered patch shape, and edge proximity—impact plant-dwelling mite communities and mite-plant-fungus interactions within a large-scale habitat fragmentation experiment. Methods We sampled mite communities from the leaves of Quercus nigra (a plant species that has foliar domatia which harbor fungivorous and predacious mites) near and far from edge within fragments of varying edge-to-area ratio (shape) and connectivity via corridors. We also performed a mite-exclusion experiment across these fragmentation treatments to test the effects of mite presence and fungal hyphal abundance on leaf surfaces. Results Habitat edges influenced the abundance and richness of leaf-dwelling mites; plants closer to the edge had higher mite abundance and species richness. Likewise, hyphal counts were higher on leaves near patch edges. Despite both mite and fungal abundance being higher at patch edges, leaf hyphal counts were not impacted by mite abundance on those leaves. Neither patch shape nor connectivity influenced mite abundance, mite species richness, or the influence of mites on leaf surface fungal abundance. Conclusion Our results suggest that mites and foliar fungi may be independently affected by edge-structured environmental gradients, like temperature, rather than trophic effects. We demonstrate that large-scale habitat fragmentation and particularly edge effects can have impacts on multiple levels of microscopic communities, even in the absence of cascading trophic effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Structural Characterization of Disulfide-Linked p53-Derived Peptide Dimers

Disulfide bonds provide a convenient method for chemoselective alteration of peptide and protein structure and function. We previously reported that mild oxidation of a p53-derived bisthiol peptide (CTFANLWRLLAQNC) under dilute non-denaturing conditions led to unexpected disulfide-linked dimers as the exclusive product. The dimers were antiparallel, significantly α-helical, resistant to protease degradation, and easily reduced back to the original bisthiol peptide. Here, in this work, we examine the intrinsic factors influencing peptide dimerization using a combination of amino acid substitution, circular dichroism (CD) spectroscopy, and X-ray crystallography. CD analysis of peptide variants suggests critical roles for Leu6 and Leu10 in the formation of stable disulfide-linked dimers. The 1.0 Å resolution crystal structure of the peptide dimer supports these data, revealing a leucine-rich LxxLL dimer interface with canonical knobs-into-holes packing. Two levels of higher-order oligomerization are also observed in the crystal: an antiparallel “dimer of dimers” mediated by Phe3 and Trp7 residues in the asymmetric unit and a tetramer of dimers mediated by Trp7 and Leu10. In CD spectra of Trp-containing peptide variants, minima at 227 nm provide evidence for the dimer of dimers in dilute aqueous solution. Importantly, and in contrast to the original dimer model, the canonical leucine-rich core and robust dimerization of most peptide variants suggests a tunable molecular architecture to target various proteins and evaluate how folding and oligomerization impact various properties, such as cell permeability.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Offshore application of landslide susceptibility mapping using gradient-boosted decision trees: a Gulf of Mexico case study

Abstract Among natural hazards occurring offshore, submarine landslides pose a significant risk to offshore infrastructure installations attached to the seafloor. With the offshore being important for current and future energy production, there is a need to anticipate where future landslide events are likely to occur to support planning and development projects. Using the northern Gulf of Mexico (GoM) as a case study, this paper performs Landslide Susceptibility Mapping (LSM) using a gradient-boosted decision tree (GBDT) model to characterize the spatial patterns of submarine landslide probability over the United States Exclusive Economic Zone (EEZ) where water depths are greater than 120 m. With known spatial extents of historic submarine landslides and a Geographic Information System (GIS) database of known topographical, geomorphological, geological, and geochemical factors, the resulting model was capable of accurately forecasting potential locations of sediment instability. Results of a permutation modelling approach indicated that LSM accuracy is sensitive to the number of unique training locations with model accuracy becoming more stable as the number of training regions was increased. The influence that each input feature had on predicting landslide susceptibility was evaluated using the SHapely Additive exPlanations (SHAP) feature attribution method. Areas of high and very high susceptibility were associated with steep terrain including salt basins and escarpments. This case study serves as an initial assessment of the machine learning (ML) capabilities for producing accurate submarine landslide susceptibility maps given the current state of available natural hazard-related datasets and conveys both successes and limitations.

Dyer, Alec S. (ORCID:0000000219813904)↗
DOE OSTI2022

Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)

First-mile last-mile (FMLM) mobility services that connect riders to public transit can lead to improved transit accessibility and network efficiency if such services are convenient and reliable. However, many current FMLM services are inefficient and costly because they are inflexible (e.g., fixed supply of shuttles) and do not leverage collected data for optimized decision making. At the same time, new forms of shared mobility can provide added flexibility and real-time analytics to FMLM systems when carefully integrated. This study evaluates performance and cost implications of public/private coordination between transit shuttles and transportation network companies (TNC) in the FMLM context. A real-time operations model was developed to simulate daily operations for an existing FMLM system using real-world demand data. Three supply strategies were tested with varying levels of flexibility: (1) Status Quo (two 23-passenger on-demand shuttles), (2) Hybrid (one 23-passenger on-demand shuttle + TNC), and (3) TNC Only (exclusively use TNC services). Results indicated that the added flexibility of the Hybrid service design (using shuttles and TNCs) improved service performance (a 7.7% improvement), reduced daily operating costs (– 6.0%), and improved service reliability (95th percentile travel times decreased by up to 40% during peak periods). In addition, the Hybrid service design was more robust to variations in demand. Here, the Hybrid service was significantly cheaper to operate (– 31.6%) at reduced demand levels (50% of normal), and improved service performance (a 10.2% improvement) when demand levels were increased (150% of normal). These findings emphasize the importance of flexibility in FMLM service designs, especially when demand is sparse and variable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗