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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Multiple indicators, multiple causes measurement error models

Multiple indicators, multiple causes (MIMIC) models are often employed by researchers studying the effects of an unobservable latent variable on a set of outcomes, when causes of the latent variable are observed. There are times, however, when the causes of the latent variable are not observed because measurements of the causal variable are contaminated by measurement error. The objectives of this study are as follows: (i) to develop a novel model by extending the classical linear MIMIC model to allow both Berkson and classical measurement errors, defining the MIMIC measurement error (MIMIC ME) model; (ii) to develop likelihood-based estimation methods for the MIMIC ME model; and (iii) to apply the newly defined MIMIC ME model to atomic bomb survivor data to study the impact of dyslipidemia and radiation dose on the physical manifestations of dyslipidemia. Finally, as a by-product of our work, we also obtain a data-driven estimate of the variance of the classical measurement error associated with an estimate of the amount of radiation dose received by atomic bomb survivors at the time of their exposure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

MCNP TREAT Core Model with MIMIC-N

This MCNP model contains the MIMIC-N materials and instrumentation test and the BUSTER containment system within the TREAT core in a full slot configuration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics

We develop physics-constrained and control-oriented predictive deep learning models for the thermal dynamics of a real-world commercial office building. The proposed method is based on the systematic encoding of physics-based prior knowledge into a structured recurrent neural architecture. Specifically, our model mimics the structure of the building thermal dynamics model and leverages penalty methods to model inequality constraints. Additionally, we use constrained matrix parameterization based on the Perron-Frobenius theorem to bound the eigenvalues of the learned network weights. We interpret the stable eigenvalues as dissipativeness of the learned building thermal model. We demonstrate the effectiveness of the proposed approach on a dataset obtained from an office building with $20$ thermal zones.

Building Energy, structured neural networks↗
DOE OSTI2022

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Here, subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a – 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Semilocal exchange hole with an application to range-separated density functionals

The exchange-correlation hole is a central concept in density functional theory. It not only provides justification for an exchange-correlation energy functional but also serves as a local ingredient for nonlocal range-separated density functionals. However, due to the nonlocal nature, modeling the conventional exact exchange hole presents a great challenge to density functional theory. In this work, we propose a semilocal exchange hole underlying the Tao-Perdew-Staroverov-Scuseria (TPSS) meta-generalized gradient approximation functional. Our model is distinct from previous ones not only at small separation between an electron and the hole around the electron but also in the way it interpolates between rapidly varying and slowly varying densities. Here the interpolation is determined by the wave-vector analysis on the infinite-barrier model for a jellium surface. Numerical tests show that our exchange-hole model mimics the conventional exact one quite well for atoms. As a simple application, we apply the hole model to construct a TPSS-based range-separated functional. We find that this range-separated functional can substantially improve the band gaps and barrier heights of TPSS, without losing much accuracy for atomization energies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Vector interaction enhanced bag model for astrophysical applications

For quark matter studies in astrophysics the thermodynamic bag model (tdBAG) has been widely used. Despite its success it fails to account for various phenomena expected from QCD. We suggest a straightforward extension of tdBAG in order to take the dynamical breaking of chiral symmetry and the influence of vector interactions explicitly into account. As for tdBAG the model mimics confinement in a phenomenological approach. It is based on an analysis of the Nambu–Jona-Lasinio (NJL) model at finite density. Furthermore, we demonstrate how NJL and bag models in this regime follow from the more general and QCD-based framework of the Dyson–Schwinger equations in a medium by assuming simple gluon contact interaction. Based on our simple and novel model, we construct quark hadron hybrid equations of state and systematically study chiral and deconfinement phase transitions, the appearance of s-quarks, and the role of vector interaction. We further study these aspects for matter in β-equilibrium at zero temperature, with particular focus on the current ∼2 M{sub ⊙} maximum mass constraint for neutron stars. Our approach indicates that the currently only theoretical evidence for the hypothesis of stable strange matter is an artifact of tdBAG and results from neglecting the dynamical breaking of chiral symmetry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Implementation of a realistic artificial data generator for crash data generation

In this paper, a framework is outlined to generate realistic artificial data (RAD) as a tool for comparing different models developed for safety analysis. The primary focus of transportation safety analysis is on identifying and quantifying the influence of factors contributing to traffic crash occurrence and its consequences. The current framework of comparing model structures using only observed data has limitations. With observed data, it is not possible to know how well the models mimic the true relationship between the dependent and independent variables. Further, real datasets do not allow researchers to evaluate the model performance for different levels of complexity of the dataset. RAD offers an innovative framework to address these limitations. Hence, we propose a RAD generation framework embedded with heterogeneous causal structures that generates crash data by considering crash occurrence as a trip level event impacted by trip level factors, demographics, roadway and vehicle attributes. Within our RAD generator we employ three specific modules: (a) disaggregate trip information generation, (b) crash data generation and (c) crash data aggregation. For disaggregate trip information generation, we employ a daily activity-travel realization for an urban region generated from an established activity-based model for the Chicago region. We use this data of more than 2 million daily trips to generate a subset of trips with crash data. For trips with crashes crash location, crash type, driver/vehicle characteristics, and crash severity. The daily RAD generation process is repeated for generating crash records at yearly or multi-year resolution. In conclusion, the crash databases generated can be employed to compare frequency models, severity models, crash type and various other dimensions by facility type - possibly establishing a universal benchmarking system for alternative model frameworks in safety literature.

42 ENGINEERING↗
DOE OSTI2020

Stoichiometrically coupled carbon and nitrogen cycling in the MIcrobial-MIneral Carbon Stabilization model version 1.0 (MIMICS-CN v1.0)

Explicit consideration of microbial physiology in soil biogeochemical models that represent coupled carbon–nitrogen dynamics presents opportunities to deepen understanding of ecosystem responses to environmental change. The MIcrobial-MIneral Carbon Stabilization (MIMICS) model explicitly represents microbial physiology and physicochemical stabilization of soil carbon (C) on regional and global scales. Here we present a new version of MIMICS with coupled C and nitrogen (N) cycling through litter, microbial, and soil organic matter (SOM) pools. The model was parameterized and validated against C and N data from the Long-Term Inter-site Decomposition Experiment Team (LIDET; six litter types, 10 years of observations, and 13 sites across North America). The model simulates C and N losses from litterbags in the LIDET study with reasonable accuracy (C: R 2 =0.63; N: R 2 =0.29), which is comparable with simulations from the DAYCENT model that implicitly represents microbial activity (C: R 2 =0.67; N: R 2 =0.30). Subsequently, we evaluated equilibrium values of stocks (total soil C and N, microbial biomass C and N, inorganic N) and microbial process rates (soil heterotrophic respiration, N mineralization) simulated by MIMICS-CN across the 13 simulated LIDET sites against published observations from other continent-wide datasets. We found that MIMICS-CN produces equilibrium values in line with measured values, showing that the model generates plausible estimates of ecosystem soil biogeochemical dynamics across continental-scale gradients. MIMICS-CN provides a platform for coupling C and N projections in a microbially explicit model, but experiments still need to identify the physiological and stoichiometric characteristics of soil microbes, especially under environmental change scenarios.

58 GEOSCIENCES↗
DOE OSTI2017

Λ( t ) cosmology induced by a slowly varying Elko field

In this work the exact Friedmann-Robertson-Walker equations for an Elko spinor field coupled to gravity in an Einstein-Cartan framework are presented. The torsion functions coupling the Elko field spin-connection to gravity can be exactly solved and the FRW equations for the system assume a relatively simple form. In the limit of a slowly varying Elko spinor field there is a relevant contribution to the field equations acting exactly as a time varying cosmological model Λ( t )=Λ{sub *}+3β H {sup 2}, where Λ{sub *} and β are constants. Observational data using distance luminosity from magnitudes of supernovae constraint the parameters Ω {sub m} and β, which leads to a lower limit to the Elko mass. Such model mimics, then, the effects of a dark energy fluid, here sourced by the Elko spinor field. The density perturbations in the linear regime were also studied in the pseudo-Newtonian formalism.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Managing Subsurface Pressure Buildup and Interference in Commercial-Scale CO 2 Storage Project with Proximal Injection Wells

Large-scale decarbonization using carbon capture and storage (CCS) is likely to involve many commercial-scale CO 2 storage projects located in close proximity to each other. This close proximity raises concerns over pressure interference among the storage projects. Pressure interference between injection and storage efforts can reduce the practicable CO 2 storage resource and force wells to inject CO 2 at a lower rate to avoid the fracture pressure thresholds per United States Environmental Protection Agency (EPA) Class VI well regulations to preserve injection and confining zone integrity and potentially mitigate against inducing seismic activity. These analyses employ numerical full-physics reservoir modeling to evaluate how pressure buildup fronts and CO 2 plumes evolve under commercial-scale injection volumes of CO 2 in which multiple storage sites located in close proximity occur in tandem. The simulation models mimic injection at pseudo basin-scale and assume homogeneous saline formation(s) as storage targets with a pair of upper and lower homogeneous seal layer/s. These analyses specifically investigate the efficacy of two basin-wide reservoir pressure management strategies in addressing the technical challenges associated with pressure buildup and CO 2 plume commingling. The strategies explored include: 1) enlarging the area of injection well spacing (WS) and 2) storing CO 2 in a stacked sequence (SSS) of saline formations compared to a single formation. The storage and confining zones properties assumed were held common across the scenarios, unless specified otherwise. Analyses results show that after injecting 4 million tons per year for 30 years using 4 separate wells (each injecting 1 million metric tons per year), the radius of CO 2 plume extends to a mere 3 km or less from injection wells. Meanwhile, the radius of pressure buildup ranges on the order of tens to a few hundreds of kilometers, depending on the magnitude of pressure buildup threshold that one would use to define the front. CO 2 plume commingling from different injection wells appears to occur 50 years post-injection, especially under scenarios with narrowly spaced (i.e., < 5 km apart) injection well locations. Findings from sensitivity cases on the well spacing suggest that storage formations modeled would require different well spacing to avoid fracture pressure thresholds. For instance, modeled storage formations with high fracture gradients (i.e., 0.8 psi/ft) would need less than 5–km well spacing, whereas those with lower fracture gradients (i.e., 0.7 psi/ft) would need approximately 20–km well spacing, based on assumed modeling parameters. Under stacked injection, the pressure challenges (described above) still exist but are more alleviated due to distributing the same injection volume across more available reservoir volume. These analyses demonstrate that stacked-sequence storage can effectively address the challenges, while still providing the same target CO 2 storage volumes and allowing a large number of storage projects to be deployed in the same basin by better utilizing the available storage resource across different reservoir depths. Among cases modeled, the resulting pressure buildup front is most suppressed when each storage project distributes injection volumes over several wells, each of which injects a portion of the total CO 2 across the stacked sequence. This strategy results in the smallest CO 2 aerial footprint amongst scenarios evaluated but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 42 percent compared to the commercial-scale single-formation storage), the result of which is crucial to maintain caprock integrity. The findings presented by this research draw attention to the importance of greater coordination among storage operators and regulatory stakeholders to foster the upscaling and deployment of CCS. These analyses provide insights into required decision-making when considering multi-project deployment in a shared basin. Because these analyses evaluate a very specific geologic situation, they bear further investigations across other geologic situations.

42 ENGINEERING↗
DOE OSTI2020

Outdoor Home Gardener Preferences for Environmental Attributes in Gardening Supplies and Use of Ecofriendly Gardening Practices

Home gardeners’ concerns for the environment are expressed both in the ecofriendly gardening practices they use and in environmental attributes they prefer in the gardening products they purchase. This study uses data from a 2018 survey of 601 Tennessee outdoor home gardeners and a multiple indicators multiple causes (MIMIC) model to illustrate how outdoor home gardener demographics, expenditures, information use, and attitudes influence use of ecofriendly gardening practices and preferences for environmental attributes in home gardening supplies. Practices considered include planting pollinator plants, using rainwater collectors, composting, recycling gardening supplies packaging, using organic gardening methods, and use of soil testing. Gardening supply product attributes include decreased need for fertilizer, pesticides, and water; native plant species; organically produced products; and recyclable packaging. The most widely used practice is recycling gardening supplies packaging, and the least used is soil testing. Gardeners with a greater propensity to use the six gardening practices include male, college graduates, who spend relatively more of their income on gardening supplies, and consider themselves as being knowledgeable about environmental issues. The gardening supply product attribute most widely considered as important is decreased need for pesticides, and least widely considered as important are native species and organically produced. Gardeners more likely to prefer the six gardening supply product attributes include older gardeners, who seek other gardeners for information, and who perceived themselves as being knowledgeable about the environment. This same group likes to grow their own food and feels responsibility for protecting the environment for future generations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Phase controlled metal–insulator transition in multi-leg quasiperiodic optical lattices

A tight-binding model of a multi-leg ladder network with a continuous quasiperiodic modulation in both the site potential and the inter-arm hopping integral is considered. The model mimics optical lattices where ultra-cold fermionic or bosonic atoms are trapped in double well potentials. It is observed that, the relative phase difference between the on-site potential and the inter-arm hopping integral, which can be controlled by the tuning of the interfering laser beams trapping the cold atoms, can result in a mixed spectrum of one or more absolutely continuous subband(s) and point like spectral measures. This opens up the possibility of a re-entrant metal–insulator transition. The subtle role played by the relative phase difference mentioned above is revealed, and we corroborate it numerically by working out the multi-channel electronic transmission for finite two-, and three-leg ladder networks. The extension of the calculation beyond the two-leg case is trivial, and is discussed in the work. - Graphical abstract: ▪ - Highlights: • Phase controlled metal–insulator transition is discussed. • An analytical prescription is given to understand MI transition. • Our work provides a way of designing experiments involving laser beams.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Acute 7,12-dimethylbenz[a]anthracene exposure causes differential concentration-dependent follicle depletion and gene expression in neonatal rat ovaries

Chronic exposure to the polycyclic aromatic hydrocarbon 7,12-dimethylbenz[a]anthracene (DMBA), generated during combustion of organic matter including cigarette smoke, depletes all ovarian follicle types in the mouse and rat, and in vitro models mimic this effect. To investigate the mechanisms involved in follicular depletion during acute DMBA exposure, two concentrations of DMBA at which follicle depletion has (75 nM) and has not (12.5 nM) been observed were investigated. Postnatal day four F344 rat ovaries were maintained in culture for four days before a single exposure to vehicle control (1% DMSO; CT) or DMBA (12 nM; low-concentration or 75 nM; high-concentration). After four or eight additional days of culture, DMBA-induced follicle depletion was evaluated via follicle enumeration. Relative to control, DMBA did not affect follicle numbers after 4 days of exposure, but induced large primary follicle loss at both concentrations after 8 days; while, the low-concentration DMBA also caused secondary follicle depletion. Neither concentration affected primordial or small primary follicle number. RNA was isolated and quantitative RT-PCR performed prior to follicle loss to measure mRNA levels of genes involved in xenobiotic metabolism (Cyp2e1, Gstmu, Gstpi, Ephx1), autophagy (Atg7, Becn1), oxidative stress response (Sod1, Sod2) and the phosphatidylinositol 3-kinase (PI3K) pathway (Kitlg, cKit, Akt1) 1, 2 and 4 days after exposure. With the exception of Atg7 and cKit, DMBA increased (P < 0.05) expression of all genes investigated. Also, BECN1 and pAKT{sup Thr308} protein levels were increased while cKIT was decreased by DMBA exposure. Taken together, these results suggest an increase in DMBA bioactivation, add to the mechanistic understanding of DMBA-induced ovotoxicity and raise concern regarding female low concentration DMBA exposures. - Highlights: • Acute DMBA exposures induce large primary and/or secondary follicle loss. • Acute DMBA exposure did not impact primordial and small primary follicle number. • Altered ovarian gene expression was observed due to DMBA exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Serum starvation of ARPE-19 changes the cellular distribution of cholesterol and Fibulin3 in patterns reminiscent of age-related macular degeneration

Highlights: • Serum deprivation regulates cholesterol levels in confluent RPE cells. • Serum deprivation leads to specific distributions of cholesterol and Fibulin3. • The patterns of protein and lipid deposition resemble those in AMD eyes. Retinal pigment epithelium (RPE) has been implicated as key source of cholesterol-rich deposits at Bruch's membrane (BrM) and in drusen in aging human eye. We have shown that serum-deprivation of confluent RPE cells is associated with upregulation of cholesterol synthesis and accumulation of unesterified cholesterol (UC). Here we investigate the cellular processes involved in this response. We compared the distribution and localization of UC and esterified cholesterol (EC); the age-related macular degeneration (AMD) associated EFEMP1/Fibulin3 (Fib3); and levels of acyl-coenzyme A (CoA): cholesterol acyltransferases (ACAT) ACAT1, ACAT2 and Apolipoprotein B (ApoB) in ARPE-19 cells cultured in serum-supplemented and serum-free media. The results were compared with distributions of these lipids and proteins in human donor eyes with AMD. Serum deprivation of ARPE-19 was associated with increased formation of FM dye-positive membrane vesicles, many of which co-labeled for UC. Additionally, UC colocalized with Fib3 in distinct granules. By day 5, serum-deprived cells grown on transwells secreted Fib3 basally into the matrix. While mRNA and protein levels of ACTA1 were constant over several days of serum-deprivation, ACAT2 levels increased significantly after serum-deprivation, suggesting increased formation of EC. The lower levels of intracellular EC observed under serum-deprivation were associated with increased formation and secretion of ApoB. The responses to serum-deprivation in RPE-derived cells: accumulation and secretion of lipids, lipoproteins, and Fib3 are very similar to patterns seen in human donor eyes with AMD and suggest that this model mimics processes relevant to disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

A model-based information sharing protocol for profile Hidden Markov Models used for HIV-1 recombination detection

Background: In many applications, a family of nucleotide or protein sequences classified into several subfamilies has to be modeled. Profile Hidden Markov Models (pHMMs) are widely used for this task, modeling each subfamily separately by one pHMM. However, a major drawback of this approach is the difficulty of dealing with subfamilies composed of very few sequences. One of the most crucial bioinformatical tasks affected by the problem of small-size subfamilies is the subtyping of human immunodeficiency virus type 1 (HIV-1) sequences, i.e., HIV-1 subtypes for which only a small number of sequences is known. Results: To deal with small samples for particular subfamilies of HIV-1, we introduce a novel model-based information sharing protocol. It estimates the emission probabilities of the pHMM modeling a particular subfamily not only based on the nucleotide frequencies of the respective subfamily but also incorporating the nucleotide frequencies of all available subfamilies. To this end, the underlying probabilistic model mimics the pattern of commonality and variation between the subtypes with regards to the biological characteristics of HI viruses. In order to implement the proposed protocol, we make use of an existing HMM architecture and its associated inference engine. Conclusions: We apply the modified algorithm to classify HIV-1 sequence data in the form of partial HIV-1 sequences and semi-artificial recombinants. Thereby, we demonstrate that the performance of pHMMs can be significantly improved by the proposed technique. Moreover, we show that our algorithm performs significantly better than Simplot and Bootscanning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A Millennium-long Evolution of the 1 yr Recurrence Period Nova—Search for Any Indication of the Forthcoming He Flash

We present 1500 cycles of hydrogen shell flashes on a 1.38 M{sub ⊙} white dwarf (WD) for a mass accretion rate of 1.6×10{sup −7} M{sub ⊙} yr{sup −1}, the mass ejection of which is calculated consistently with the optically thick winds. This model mimics the 1 yr recurrence period nova M31N 2008-12a. Through these hydrogen flashes a helium ash layer grows in mass and eventually triggers a helium nova outburst. Each hydrogen flash is almost identical, and there is no precursor for the forthcoming He flash either in the outburst or in the quiescent until the next He flash suddenly occurs. Thus, M31N 2008-12a is a promising candidate of He novae, outbursting in any time within a millennium. The prompt X-ray flash of He nova lasts as short as 15 minutes, with the X-ray luminosity being about half of the Eddington luminosity, making the observation difficult. In the very early phase of a He flash, the uppermost H-rich layer is convectively mixed into the deep interior and most of the hydrogen is consumed by nuclear burning. In comparison with hydrogen shell flashes of M31N 2008-12a, we expect the forthcoming He nova to have a very short prompt X-ray flash (15 minutes), a very bright optical/near-IR peak (∼3.5 mag brighter than M31N 2008-12a), a much longer nova duration (>2 yr), and a longer supersoft X-ray source phase (40–50 days or more).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The RISMC Approach to Perform Advanced PRA Analyses

The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these two factors on the safety of the plant, the RISMC Pathway aims to develop simulation-based tools and methods to assess risks for existing nuclear power plants in order to optimize safety. This pathway, by developing new methods, is extending the state-of-the-practice methods that have been traditionally based on logic structures such as Event-Trees and Fault-Trees. These static types of models mimic system response in an inductive and deductive way respectively, yet are restrictive in the ways they can represent spatial and temporal constructs. RISMC analyses are performed by using a combination of thermal-hydraulic codes and a stochastic analysis tool currently under development at the Idaho National Laboratory, i.e. RAVEN. This paper presents a case study in order to show the capabilities of the RISMC methodology to assess impact of power uprate of a boiling water reactor system during a station blackout accident scenario. We employ the system simulator code, RELAP5-3D, coupled with RAVEN which perform the stochastic analysis. Our analysis is in fact performed by: 1) sampling values of a set of parameters from the uncertainty space of interest, 2) simulating the system behavior for that specific set of parameter values and 3) analyzing the set of simulation runs. Results obtained give a detailed investigation of the issues associated with a plant power uprate including the effects of station blackout accident scenarios. We are able to quantify how the timing of specific events was impacted by a higher nominal reactor core power. Such safety insights can provide useful information to the decision makers to perform risk informed margins management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The supersymmetric Georgi-Machacek model

We show that the well known Georgi-Machacek (GM) model can be realized as a limit of the recently constructed Supersymmetric Custodial Higgs Triplet Model (SCTM) which in general contains a significantly more complex scalar spectrum. We dub this limit of the SCTM, which gives a weakly coupled origin for the GM model at the electroweak scale, the Supersymmetric GM (SGM) model. We derive a mapping between the SGM and GM models using it to show how a supersymmetric origin implies constraints on the Higgs potential in conventional GM model constructions which would generically not be present. We then perform a simplified phenomenological study of diphoton and ZZ signals for a pair of benchmark scenarios to illustrate under what circumstances the GM model can mimic the SGM model and when they should be easily distinguishable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗