Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dynamic timing analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44

Simulating Z 2 lattice gauge theory on a quantum computer

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of Z 2 gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of 6 and is therefore essential for obtaining reliable masses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗

Observational evidence for groundwater influence on crop yields in the United States

As climate change shifts crop exposure to dry and wet extremes, a better understanding of factors governing crop response is needed. Recent studies identified shallow groundwater—groundwater within or near the crop rooting zone—as influential, yet existing evidence is largely based on theoretical crop model simulations, indirect or static groundwater data, or small-scale field studies. Here, we use observational satellite yield data and dynamic water table simulations from 1999 to 2018 to provide field-scale evidence for shallow groundwater effects on maize yields across the United States Corn Belt. We identify three lines of evidence supporting groundwater influence: 1) crop model simulations better match observed yields after improvements in groundwater representation; 2) machine learning analysis of observed yields and modeled groundwater levels reveals a subsidy zone between 1.1 and 2.5 m depths, with yield penalties at shallower depths and no effect at deeper depths; and 3) locations with groundwater typically in the subsidy zone display higher yield stability across time. We estimate an average 3.4% yield increase when groundwater levels are at optimum depth, and this effect roughly doubles in dry conditions. Groundwater yield subsidies occur ~35% of years on average across locations, with 75% of the region benefitting in at least 10% of years. Overall, we estimate that groundwater-yield interactions had a net monetary contribution of approximately $10 billion from 1999 to 2018. This study provides empirical evidence for region-wide groundwater yield impacts and further underlines the need for better quantification of groundwater levels and their dynamic responses to short- and long-term weather conditions.

60 APPLIED LIFE SCIENCES↗

Time-Resolved X-ray Emission Spectroscopy and Synthetic High-Spin Model Complexes Resolve Ambiguities in Excited-State Assignments of Transition-Metal Chromophores: A Case Study of Fe-Amido Complexes

To fully harness the potential of abundant metal coordination complex photosensitizers, a detailed understanding of the molecular properties that dictate and control the electronic excited-state population dynamics initiated by light absorption is critical. In the absence of detectable luminescence, optical transient absorption (TA) spectroscopy is the most widely employed method for interpreting electron redistribution in such excited states, particularly for those with a charge-transfer character. The assignment of excited-state TA spectral features often relies on spectroelectrochemical measurements, where the transient absorption spectrum generated by a metal-to-ligand charge-transfer (MLCT) electronic excited state, for instance, can be approximated using steady-state spectra generated by electrochemical ligand reduction and metal oxidation and accounting for the loss of absorptions by the electronic ground state. However, the reliability of this approach can be clouded when multiple electronic configurations have similar optical signatures. Using a case study of Fe(II) complexes supported by benzannulated diarylamido ligands, we highlight an example of such an ambiguity and show how time-resolved X-ray emission spectroscopy (XES) measurements can reliably assign excited states from the perspective of the metal, particularly in conjunction with accurate synthetic models of ligand-field electronic excited states, leading to a reinterpretation of the long-lived excited state as a ligand-field metal-centered quintet state. Furthermore, a detailed analysis of the XES data on the long-lived excited state is presented, along with a discussion of the ultrafast dynamics following the photoexcitation of low-spin Fe(II)-N amido complexes using a high-spin ground-state analogue as a spectral model for the 5 T 2 excited state.

14 SOLAR ENERGY↗

Study of the water dynamics near hydrophilic, nanostructured CuO surfaces by quasielastic and inelastic neutron scattering

We have used quasielastic and inelastic neutron scattering to investigate the structure, dynamics, and phase transitions of water interacting with superhydrophilic CuO surfaces that not only possess a strong affinity for water but also a “grass-like” topography that is rough on both micro- and nanoscales. Here, we report quasielastic neutron scattering (QENS) measurements on two samples differing in water content at five temperatures below 280 K. The QENS spectra show water undergoing two different types of diffusive motion near the CuO surfaces: a “slow” translational diffusion occurring on a nanosecond time scale and a faster rotational motion. Further from the surfaces, there is “fast” translational diffusion comparable in rate to that of bulk supercooled water and the rotational motion occurring in the interfacial water. Analysis of the QENS spectra supports wetting of water to the CuO blades as seen in electron microscopy images. In addition, we observe an anomalous temperature dependence of the QENS spectra on cooling from 270 to 230 K with features consistent with a liquid–liquid phase transition. We suggest that the solvent-like properties of the coexisting bulk-like water in our CuO samples are a significant factor in determining the temperature dependence of the interfacial water’s dynamics. Our results are compared with those obtained from two well-studied substrate classes: (1) silicas that contain ordered cylindrical nanopores but have weaker hydrophilicity and (2) nanoparticles of other transition-metal oxides, such as TiO 2 , which share the strong hydrophilicity of our samples but lack their porosity.

36 MATERIALS SCIENCE↗

Holistic Small-Signal Stability Analysis for Large-Scale Inverter-Intensive Power Systems with Coupled and Full-Order Dynamics from Control Systems and Power Networks

The increasing penetration of inverter-based resources (IBRs) into the existing power systems introduces tremendous benefits for enhanced sustainability but also poses inevitable challenges in terms of insufficient inertia, potential instability, and complex network dynamics, among others. However, the additional coupling introduced by the interactions among gridfollowing (GFL) and grid-forming (GFM) IBRs and the other components (i.e., synchronous generators [SGs], loads, and network, etc.) has not been clearly explored. A holistic, scalable, and quantitative stability analysis framework with the control systems and power networks is still missing. Here, in this paper, to fill in the technical gaps, a holistic small-signal model of the entire system with both rotating generation units and IBRs is established. An extended power flow model with operation dynamics from both generator control schemes and power networks is proposed to provide the varying steady-state operating points for small-signal modeling. The proposed method is compared with MATLAB solvers, and the results show that the proposed approach has a minimum calculation time, which can be less than 12 seconds for a large-scale power system with up to 2,000 buses. Furthermore, a quantitative method is developed to identify the impacts of IBRs on system performance with emphases on the potential stability issues with GFL IBRs, additional benefits of employing GFM IBRs, the feasibility of replacing SGs with GFM IBRs, and the impact of penetration level of different kinds of generation units. Finally, a field island power system is used to verify the proposed approach, and hardware-in-the-loop (HIL) tests are provided to further demonstrate the effectiveness of the proposed analysis.

14 SOLAR ENERGY↗

Phonon modal analysis of thermal transport in ThO 2 with point defects using equilibrium molecular dynamics

Defects can significantly degrade the thermal conductivity of ThO 2 , an advanced nuclear fuel material as well as a surrogate for other fluorite-structured materials. Here, we investigate how point defects in ThO 2 impact phonon mode-resolved thermal transport. By incorporating phonon modes from lattice dynamics, we decompose the trajectory and heat flux to phonon normal mode space and extract key phonon properties, including phonon relaxation times and their contributions to thermal conductivity. We implement two methods. The first method is based on the Green Kubo formalism to resolve the contribution of each phonon mode to thermal conductivity. The second resolves the lifetime of individual phonon modes and the thermal conductivity is calculated using the Boltzmann transport equation within relaxation time approximation. Notably, a lower contribution of acoustic modes is revealed compared to perturbative approaches considering only three-phonon scattering processes. The effects of four types of point defects are evaluated. The strongest impact on a reduction in thermal conductivity is from Th interstitials, followed by Th vacancies. O interstitials/vacancies have a similar impact, albeit smaller than defects on the thorium sublattice. These observations are consistent with previous studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗

Implications of inertial subrange scaling for stably stratified mixing

In this work, we investigate the effects of the turbulent dynamic range on active scalar mixing in stably stratified turbulence by adapting the theoretical passive scalar modelling and demonstrating their usefulness through consideration of the results of direct numerical simulations of statistically stationary homogeneous stratified and sheared turbulence. By analysis of inertial and inertial–convective subrange scalings, we show that the relationship between the active scalar and turbulence time scales is predicted by the ratio of the Kolmogorov and Obukhov–Corrsin constants, provided mean flow parameters permit the two subrange scalings to be appropriate approximations. We use the resulting relationship between time scales to parameterise an appropriate turbulent mixing coefficient $\varGamma \equiv \chi /\epsilon$, defined here as the ratio of available potential energy ($E_p$) and turbulent kinetic energy ($E_k$) dissipation rates. With the analysis presented here, we show that $\varGamma$ can be estimated by $E_p,E_k$ and a universal constant provided an appropriate Reynolds number is sufficiently high. This large Reynolds number regime appears here to occur at $ {{Re_b}} \equiv \epsilon / \nu N^{2} \gtrapprox 300$ where $\nu$ is the kinematic viscosity and $N$ is the characteristic buoyancy frequency. We propose a model framework for irreversible diapycnal mixing with robust theoretical parametrisation and asymptotic behaviour in this high-$ {{Re_b}}$ limit.

42 ENGINEERING↗

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗

The five line-of-sight neutron time-of-flight (nToF) suite on the National Ignition Facility (NIF)

Measurement of the neutron spectrum from inertial confinement fusion implosions is one of the primary diagnostics of implosion performance. Analysis of the spectrum gives access to quantities such as neutron yield, hot-spot velocity, apparent ion temperature, and compressed fuel ρr through measurement of the down-scatter ratio. On the National Ignition Facility, the neutron time-of-flight suite has been upgraded to include five independent, collimated lines of sight, each comprising a high dynamic range bibenzyl/diphenylacetylene-stilbene scintillator [R. Hatarik et al., Plasma Fusion Res. 9, 4404104 (2014)] and high-speed fused silica Cherenkov detectors [A. S. Moore et al., Rev. Sci. Instrum. 89, 10I120 (2018)].

Moore, A. S. (ORCID:0000000221258882)↗

On hybrid scenarios in KSTAR

We report the status of hybrid scenario experiments in Korea Superconducting Tokamak Advanced Research (KSTAR). The hybrid scenario is defined as stationary discharges with ${\beta _{\rm{N}}}$ $ \geqslant $ 2.4 and ${H_{89}}$ $ \geqslant $ 2.0 at ${q_{95}}$ < 6.5 without or with very mild sawtooth activities in KSTAR. It is being developed towards reactor-relevant conditions. High performance of ${\beta _{\rm{N}}} \lesssim 3.0$, ${H_{89}} \lesssim 2.4$ and G-factor ($ \equiv {\beta _{\rm{N}}}{H_{89}}/q_{95}^2$) $ \lesssim 0.4$6 has been achieved and sustained for $ \gtrsim 40{{\tau }_{\text{E}}}$ at ne/nGW ~ 0.7 with heating power of $ \lesssim $5 MW. Some KSTAR hybrid discharges exhibit a unique feature of a slow transition from conventional H-mode to hybrid mode after the third neutral beam injection. The reason for the confinement enhancement is extensively studied in this transition period of a representative discharge exhibiting a common feature of KSTAR hybrid scenarios. 0D performance analysis with magnetohydrodynamic activities, 1D kinetic profile dynamics, power balance analysis, linear gyro-kinetic analysis and edge pedestal stability analysis were conducted. The enhancement is thought to be from both the core and the pedestal. The improvement in the core region of the ion energy channel is observed from the linear gyro-kinetic analysis considering the electromagnetic, the fast ion, the Shafranov shift, ${\it{\omega }_{E \times B}}$, and the magnetic shear effect. The electromagnetic finite $\beta $ stabilisation plays a role in the inner core region at ${\rho _{\rm{tor}}}\sim0.35$ together with the fast ion effect. The alpha stabilisation effect is also found at ${\rho _{\rm{tor}}}\sim0.5$. ${\omega _{E \times B}}$, which could reduce the linear growth of the ion temperature gradient mode in the outer core region at ${\rho _{\rm{tor}}}\sim0.5 - 0.7$ with the highest contribution from the toroidal rotation. Furthermore, regarding the improvement in the pedestal, Shafranov shift broadens the stability boundary of the pedestal in support of the diamagnetic effect. The pedestal height and width could be reproduced by the EPED model, while a realistic current profile is used to calculate the internal inductance for Shafranov shift. Based on these findings, a comprehensive confinement enhancement mechanism has been proposed by considering the core-edge interplay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ultrafast Inverse Chirality-Induced Spin Selectivity Observed by THz Emission

Chirality-induced spin selectivity (CISS) phenomena arise from an interplay among structural chirality, electron spin orientation, and charge current. Steady-state observations such as magnetoresistance offer little insight into the timescales that govern the spin-charge interconversion and often conflate interfacial and bulk phenomena. By contrast, inverse CISS involves the conversion of spin to a charge current. Using terahertz (THz) emission spectroscopy, we directly measured an ultrafast charge current due to inverse CISS with picosecond time resolution. Polarity and polarization analysis of the THz emission map the induced charge current direction upon spin injection. We found that a charge current is generated along the spin orientation that changes direction with stereochemical configuration. These observations directly demonstrate the inherent coupling between spin and charge currents in chiral systems, offering key insights into their fundamental dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Approximate Entropy Analysis for Nonlinear Beam Dynamics

In this paper, we applied an approximate entropy (ApEn) analysis to nonlinear beam dynamics. Due to the presence of strong nonlinear magnets, the degree of chaos in beam motion gradually increases proportionally with its amplitude. Such chaos can be quantitatively characterized with ApEn of beam turn-by-turn readings. ApEn analysis is a technique used to quantify the amount of regularity and the unpredictability of fluctuations with respect to time-series data. The ApEn, when applied as a chaos indicator, can then be used for nonlinear lattice optimization and analysis. The National Synchrotron Light Source II (NSLS-II) electron storage ring lattice was used as an example of a real-world application of our technique.

43 PARTICLE ACCELERATORS↗

Modeling FLEX Human Actions Using the EMRALD Dynamic Risk Assessment Tool

Most current efforts have modified and applied existing human reliability analysis (HRA) methods to treat human actions related to beyond-design-basis external events in which diverse and flexible coping strategies (FLEX) equipment would be deployed. However, many questions remain regarding the suitability of legacy HRA methods to address FLEX human actions, sparking the need for a new method of reasonably evaluating them. In this context, Idaho National Laboratory (INL) researched a relatively new approach to treating FLEX human actions via Event Modeling Risk Assessment Using Linked Diagrams (EMRALD) software. EMRALD was developed to support the increasing need for dynamic probabilistic risk assessment (PRA) models that can respond to evolving plant conditions during simulations. A couple benefits were identified when analyzing FLEX human actions through this software. In general, it is especially useful for evaluating a strategy’s feasibility, including FLEX human actions that require a relatively long time to perform. In this paper, we suggest how FLEX human actions can be modeled using the EMRALD software. Two different HRA modeling approaches using EMRALD are introduced: (1) procedure-based modeling and (2) PRA/HRA-based modeling. The former approach was introduced in the authors’ previous paper, whereas this paper mainly discusses how the latter approach works for an extended loss of AC power (ELAP) scenario with relevant procedures and PRA models. A hybrid method combining the two modeling approaches is introduced at the paper’s conclusion.

99 GENERAL AND MISCELLANEOUS↗

Examination of Semi-Analytical Solution Methods in the Coarse Operator of Parareal Algorithm for Power System Simulation

With continuing advances in high-performance parallel computing platforms, parallel algorithms have become powerful tools for development of faster than real-time power system dynamic simulations. In particular, it has been demonstrated in recent years that parallel-in-time (Parareal) algorithms have the potential to achieve such an ambitious goal. Here, the selection of a fast and reasonably accurate coarse operator of the Parareal algorithm is crucial for its effective utilization and performance. This paper examines semi-analytical solution (SAS) methods as the coarse operators of the Parareal algorithm and explores performance of the SAS methods to the standard numerical time integration methods. Two promising time-power series-based SAS methods were considered; Adomian decomposition method and Homotopy analysis method with a windowing approach for improving the convergence. Numerical performance case studies on 10-generator 39-bus system and 327-generator 2383-bus system were performed for these coarse operators over different disturbances, evaluating the number of Parareal iterations, computational time, and stability of convergence. All the coarse operators tested with different scenarios have converged to the same corresponding true solution (if they are convergent) and the SAS methods provide comparable computational speed, while having more stable convergence to the true solution in many cases.

97 MATHEMATICS AND COMPUTING↗

Low Peripheral Blood Counts and Elevated Proinflammatory Cytokines Signal a Poor CD19 Chimeric Antigen Receptor T-cell Response in Acute Lymphoblastic Leukemia

CD19 chimeric antigen receptor T-cell (CAR-T) therapy has significantly improved outcomes for patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL). However, approximately 20% of patients fail to achieve a complete remission (CR), and some develop severe, life-threatening toxicities. Understanding the biological mechanisms underlying both dysfunctional responses and severe toxicity is essential for optimizing patient management and improving therapeutic efficacy. This study aimed to (1) characterize cytokine profiles associated with dysfunctional responses and severe toxicity following CAR-T infusion, (2) examine the timing and trajectory of cytokine changes in relation to treatment outcomes, and evaluate potential strategies for mitigating toxicity and treatment failure. We conducted a comprehensive analysis of serum cytokine profiles in 86 adult and pediatric patients undergoing autologous CD19 CAR-T therapy for B-ALL. Patients were categorized into three groups: (1) Dysfunctional response—Patients who failed to achieve a minimal residual disease-negative CR (MRD-CR) by Day 63 or who experienced recurrence of CD19+ disease in the setting ongoing CAR-T cell detection before Day 63. (2) Functional response with severe cytokine release syndrome (CRS) and/or neurotoxicity (NTX)—Patients with best response of MRD-CR by Day 63 who experienced grade 3 or higher CRS or NTX. (3) Functional response without severe CRS or NTX—Patients with best response of MRD-CR by Day 63 who did not experience grade =3 CRS or NTX. Cytokine levels were measured during the first-week postinfusion and correlated with treatment efficacy, toxicity outcomes, complete blood counts, and CAR-T expansion dynamics. This analysis aimed to better understand how cytokine profiles relate to patient outcomes and immune responses in CAR-T therapy. Patients with dysfunctional response exhibited decreased neutrophils, platelets, and levels of granulocytic cytokines (suggestive of low bone marrow reserve) alongside elevated pro-inflammatory cytokines by Day 1. Functional response with severe toxicity patients showed a progressive rise in proinflammatory cytokines, reaching similar levels to dysfunctional response patients by Day 7. We observed that high cytokines at both the Day 1 and Day 7 time points were associated with poor survival. These findings remained significant when adjusting for high disease burden, a known predictor of severe inflammatory toxicity and lack of response. Early post-CAR-T infusion inflammation is associated with both dysfunctional response and severe toxicity—even after adjusting for disease burden. This suggests that inflammation, in addition to disease burden, plays a role in determining patient outcome. Therefore, strategies aimed at reducing the pro-inflammatory state prior to or early after CAR-T cell infusion may improve outcomes for R/R B-ALL patients.

Serum cytokines↗

Many-body expansion for light nuclear systems

Here we extend the many-body expansion (MBE), previously applied to hydrogen bonded and molecular systems, to the light nuclear systems 3 H and 3 He by considering the nucleonic degrees of freedom as fundamental in the expansion. The analysis is based on the Pauli nucleonic dynamics (PND) model, a simple antisymmetrized dynamical code, inspired by the sophisticated constrained molecular dynamics (CoMD) model. The total energy of the 2 H nucleus is calculated with this model at -2.312 MeV, which is within 4% of the experimental value of -2.225 MeV. The application of the MBE yields results for the three-body term in the 3 H nucleus that is comparable with previous estimates, while it is reported for the first time for the nucleus of 3 He . The energies of 3 H and 3 He that include the sum of the one- and two-body terms with the model are - 6.97 ± 0.21 MeV and - 6.19 ± 0.21 MeV and the three-body terms, estimated from the difference of the sum of the one- and two-body terms from the experimentally measured energies, are -1.51 ± 0.21 MeV and -1.53 ± 0.21 MeV, respectively. The MBE for the 3 H and 3 He nuclei is qualitatively similar to the one previously reported for the water trimer: the two- and three-body terms are negative with the latter amounting to ~3% of the former. Additionally, the three-body terms correspond to about 16–23% of the total energy of the bound systems, a percentage that is also comparable to the one in the water trimer (17%). In this manner, the MBE analysis can be applied to light nuclear systems following the same protocol as the one that has been previously extensively used for hydrogen bonded molecular systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗