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At least 415 records · Page 23

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DOE OSTI2023

Comparative Analysis of Standard and Advanced USL Methodologies for Nuclear Criticality Safety

The American National Standards Institute/American Nuclear Society national standards 8.1 and 8.24 provide guidance on the requirements and recommendations for establishing confidence in the results of the computerized models used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving freedom to the analysts to determine how the various sources of uncertainties are to be statistically aggregated. Due to the involved use of statistics entangled with heuristic recipes, the resulting safety margins are often difficult to interpret. Also, these technical margins are augmented by additional administrative margins, which are required to ensure compliance with safety standards or regulations, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems, e.g., advanced reactors, fuel cycles, and fuel concepts, focused on economizing operation, there is a strong need to develop a clear understanding of the uncertainties and their consolidation methods to reduce them in manners that can be scientifically defended. In response, the current studies compare the analyses behind four notable methodologies for upper subcriticality limit estimation that have been documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Specifically, the work offers a deep dive into the various assumptions of the noted methodologies, their adequacies, and their limitations to provide guidance on developing confidence for the emergent nuclear systems that are expected to be challenged by the scarcity of experimental data. Here, to limit the scope, the current work focuses on the application of these methodologies to criticality safety experiments, where the goal is to calculate a bias, a bias uncertainty, and a tolerance limit for k eff in support of determining an upper subcriticality limit for nuclear criticality safety.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗

DOE OSTI2022

Comparing the economic performance of ice storage and batteries for buildings with on-site PV through model predictive control and optimal sizing

Integrating renewable energy and energy storage systems provides a way of operating the electrical grid system more energy efficiently and stably. Thermal storage and batteries are the most common devices for integration. However, it is not clear which integrated storage system performs better in terms of overall economics. Ice storage has low initial and maintenance costs, but there is an efficiency penalty for charging of storage and it can only shift electrical loads associated with building cooling requirements. A battery's round-trip efficiency, on the contrary, is quite consistent and batteries can be used to shift both HVAC and non-HVAC loads. However, batteries have greater initial costs and a shorter life. Finally, this research presents a tool, using model predictive control and optimal sizing, and provides a case study for comparing life-cycle economics of battery and ice storage systems for commercial buildings that have chillers for cooling and an on-site photovoltaic system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Do people spend travel time the way they think they would? a comparative study of generic and trip-specific travel time allocation using hybrid multiple discrete continuous (MDC) framework

Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. Finally, the heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Comparative analysis of the sensitivity of nanometallic thin film thermometers

Thin film platinum resistive thermometers are conventionally applied for resistance thermometry techniques due to their stability and proven measurement accuracy. Depending upon the required thermometer thickness and temperature measurement, however, performance benefits can be realized through the application of alternative nanometallic thin films. Herein, a comparative experimental analysis is provided on the performance of nanometallic thin film thermometers most relevant to microelectronics and thermal sensing applications: Al, Au, Cu, and Pt. Sensitivity is assessed through the temperature coefficient of resistance, measured over a range of 10–300 K for thicknesses nominally spanning 25–200 nm. In this work, the interplay of electron scattering sources, which give rise to the temperature-dependent TCR properties for each metal, are analyzed in the framework of a Mayadas–Shatzkes based model. Despite the prevalence of evaporated Pt thin film thermometers, Au and Cu films fabricated in a similar manner may provide enhanced sensitivity depending upon thickness. These results may serve as a guide as the movement toward smaller measurement platforms necessitates the use of smaller, thinner metallic resistance thermometers.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization

The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200 000 integrated design evaluations were performed exploring the trade-offs between capital cost minimization and operational reliability (maximizing q 95 ) while satisfying engineering constraints including 250 ± 50 MW net electric power, tritium breeding ratio > 1.1, power exhaust limits and an hour flattop time. Both configurations achieve similar cost-performance Pareto fronts through contrasting design philosophies. PT, while demonstrating resilience to pedestal degradation (compensating for up to 40% reduction), are constrained to larger machines (R 0 > 6.5 m) by the narrow operational window between L–H threshold requirements and the research-established power exhaust limit (P sol /R < 15 MW m –1 ). This forces optimization through comparatively reduced magnetic field (∼8 T). NT configurations exploit their freedom from these constraints to access compact, high-field designs (R 0 ~ 5.5 m, B 0 >12 T), creating natural synergy with advancing HTS technology. Sensitivity analyses reveal that PT’s economic viability depends critically on uncertainties in L–H threshold scaling and power handling limits. Notably, a 50% variation in either could eliminate viable designs or enable access to the compact design space. These results suggest configuration selection should be risk-informed: PT offers the lowest-cost path when operational constraints can be confidently predicted, while NT is robust to large variations in constraints and physics uncertainties.

FUSE framework↗

DOE OSTI2020

Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms

We present a comparison of methods for uncertainty quantification (UQ) in deep learning algorithms in the context of a simple physical system. Three of the most common uncertainty quantification methods - Bayesian Neural Networks (BNN), Concrete Dropout (CD), and Deep Ensembles (DE) - are compared to the standard analytic error propagation. We discuss this comparison in terms endemic to both machine learning ("epistemic" and "aleatoric") and the physical sciences ("statistical" and "systematic"). The comparisons are presented in terms of simulated experimental measurements of a single pendulum - a prototypical physical system for studying measurement and analysis techniques. Our results highlight some pitfalls that may occur when using these UQ methods. For example, when the variation of noise in the training set is small, all methods predicted the same relative uncertainty independently of the inputs. This issue is particularly hard to avoid in BNN. On the other hand, when the test set contains samples far from the training distribution, we found that no methods sufficiently increased the uncertainties associated to their predictions. This problem was particularly clear for CD. In light of these results, we make some recommendations for usage and interpretation of UQ methods.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Validating and Comparing Energy Estimation Methods at Water Resource Recovery Facilities

Water resource recovery facilities play a crucial role in the water-energy nexus, consuming a substantial amount of energy in the United States. Growing treatment volumes and more stringent water quality standards are expected to increase the amount of energy needed to treat wastewater, but accurately estimating energy consumption and potential remains challenging due to variability in scale, treatment methods, and effluent treatment standards. In this study, we used publicly available data to evaluate the accuracy of methods for estimating energy consumption and generation, then quantified uncertainty based on key factors like flow rate, treatment level, and geographic location. To validate methods, we estimated energy consumption and generation at the facility-level, then compared estimates to self-reported data from utilities in major U.S. cities. We found that process models of treatment trains under best practice configurations were accurate relative to other methods for estimating electricity use, total energy use, and electricity generation from biogas utilization, and less complex methods based on effluent treatment level and prime movers also performed well for estimating electricity consumption and generation, respectively. Applying the evaluated methods to a national inventory of treatment facilities, we estimate that annual energy consumption ranged from 56.3 x 10^3 to 82.5 x 10^3 TJ in 2012 and 83.6 x 10^3 to 127 x 10^3 TJ in 2042. Our results indicate that not all estimation methods are suited for every use case, so we recommend that researchers and practitioners select an estimation method based on data availability and desired computational intensity.

Hodson, Abigayle↗

DOE OSTI2025

Identification of candidate host-specificity genes in Exserohilum turcicum using comparative genomics and transcriptomics

Abstract Exserohilum turcicum causes northern corn leaf blight and sorghum leaf blight. While the same species cause disease in both crops, the strains are host-specific. Here, we report the sequence and de novo annotated assemblies of one sorghum- and one maize-specific E. turcicum strain. The strains were sequenced using the PacBio Sequel II system. The total genome length for both assemblies was between 44 and 45 Mb with N50 of ∼2.5 Mb. Ninety-eight percent of the Benchmarking Universal Single-Copy Orthologs (BUSCO) for both assemblies had complete status. The estimated number of genes was 11,762 and 12,029 in the sorghum- and maize-specific isolates, respectively. Funannotate, EffectorP, SignalP, and transcriptome data were used to create functional annotation of each genome. The whole-genome comparison identified ten large-scale inversions and three translocations between the maize- and sorghum-specific strains, along with homologous genes and gene duplications. RNA was sequenced from the maize- and sorghum-specific isolate 10 days post-inoculation in maize and sorghum and from axenic cultures. Gene expression data from planta and axenic growth experiments were compared for each strain. Candidate host-specificity genes were identified by combining results from whole-genome comparison, synteny analysis, gene annotations, and transcriptome data. Overall, this study identified several candidate host-specificity genes that provide insights into E. turcicum interaction with its hosts.

Krone, Mara J. (ORCID:0000000159006624)↗

DOE OSTI2021

Comparing galaxy formation in the L-GALAXIES semi-analytical model and the IllustrisTNG simulations

ABSTRACT We perform a comparison, object by object and statistically, between the Munich semi-analytical model, L-GALAXIES, and the IllustrisTNG hydrodynamical simulations. By running L-GALAXIES on the IllustrisTNG dark matter-only merger trees, we identify the same galaxies in the two models. This allows us to compare the stellar mass, star formation rate, and gas content of galaxies, as well as the baryonic content of subhaloes and haloes in the two models. We find that both the stellar mass functions and the stellar masses of individual galaxies agree to better than ${\sim} 0.2\,$dex. On the other hand, specific star formation rates and gas contents can differ more substantially. At z = 0, the transition between low-mass star-forming galaxies and high-mass quenched galaxies occurs at a stellar mass scale ${\sim} 0.5\,$dex lower in IllustrisTNG than that in L-GALAXIES. IllustrisTNG also produces substantially more quenched galaxies at higher redshifts. Both models predict a halo baryon fraction close to the cosmic value for clusters, but IllustrisTNG predicts lower baryon fractions in group environments. These differences are primarily due to differences in modelling feedback from stars and supermassive black holes. The gas content and star formation rates of galaxies in and around clusters and groups differ substantially, with IllustrisTNG satellites less star forming and less gas rich. We show that environmental processes such as ram-pressure stripping are stronger and operate to larger distances and for a broader host mass range in IllustrisTNG. We suggest that the treatment of galaxy evolution in the semi-analytic model needs to be improved by prescriptions that capture local environmental effects more accurately.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A comparative analysis of the chemical compositions of Gaia-Enceladus/Sausage and Milky Way satellites using APOGEE

ABSTRACT We use data from the 17th data release of the Apache Point Observatory Galactic Evolution Experiment (APOGEE 2) to contrast the chemical composition of the recently discovered Gaia Enceladus/Sausage system (GE/S) to those of 10 Milky Way (MW) dwarf satellite galaxies: LMC, SMC, Boötes I, Carina, Draco, Fornax, Sagittarius, Sculptor, Sextans, and Ursa Minor. Our main focus is on the distributions of the stellar populations of those systems in the [Mg/Fe]–[Fe/H] and [Mg/Mn]–[Al/Fe] planes, which are commonly employed in the literature for chemical diagnosis and where dwarf galaxies can be distinguished from in situ populations. We show that, unlike MW satellites, a GE/S sample defined purely on the basis of orbital parameters falls almost entirely within the locus of ‘accreted’ stellar populations in chemical space, which is likely caused by an early quenching of star formation in GE/S. Due to a more protracted history of star formation, stars in the metal-rich end of the MW satellite populations are characterized by lower [Mg/Mn] than those of their GE/S counterparts. The chemical compositions of GE/S stars are consistent with a higher early star formation rate (SFR) than MW satellites of comparable and even higher mass, suggesting that star formation in the early universe was strongly influenced by other parameters in addition to mass. We find that the direction of the metallicity gradient in the [Mg/Mn]–[Al/Fe] plane of dwarf galaxies is an indicator of the early SFR of the system.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

State-level suicide mortality insights: a comparative study of VHA veterans and the whole US population

Background: Suicide is a leading cause of death in the US Comparative State-level spatial analysis between Veterans Health Administration (VHA veterans) and the whole US population can reveal differences in conditions for targeted interventions and intricate geographical patterns. Methods: The study population contains 2018 and 2019 suicide deaths of VHA veterans and the whole US population. They were used to calculate state-level rates. States were classified by whether their VHA veteran and whole US population rates were above or below respective mean rates. Local Moran’s I was leveraged to examine spatial autocorrelation. Results: State-level suicide mortality rates and disparities among states were generally higher for VHA veterans (2018: 37.3 ± 7.2; 2019: 46.8 ± 8.3) than for the whole US population (2018: 16.6 ± 4.3; 2019: 16.4 ± 4.4). For both populations, there were statistically significant clusters with high suicide rates. Over one-fourth of states demonstrated inverse relationships, with rates above mean for one group but below for other. VHA veterans are at higher risk with over one-third of states had greater than average veteran suicide risk ratio. Conclusions: VHA veterans are at higher risk than the whole population across all states. Mortality disparities among states and clusters of states with high and low rates suggest targeted interventions and cooperative health strategies may help address these differences.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression

Our objective is to demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns. For Operation Enduring Freedom/Operation Iraqi Freedom veterans with major depressive disorder, we generate pharmacotherapy pathways (of antidepressants) using process mining and machine learning. We select the medication episodes that were started at subtherapeutic doses by the first assigned primary care physician and observe the paths that those medication episodes follow. Using 2-stage least squares, we test the effectiveness of starting at a low dose and staying low for longer versus ramping up fast while balancing observable and unobservable characteristics of patients and providers through instrumental variables. We leverage predetermined provider practice patterns as instruments. We collected outpatient pharmacy data for selective serotonin reuptake inhibitors and selective norepinephrine reuptake inhibitors, patient and provider characteristics (as control variables), and the instruments for our cohort. All data were extracted for the period between 2006 and 2020. There is a statistically significant positive effect (0.68, 95% CI 0.11–1.25) of “ramping up fast” on engagement in care. When we examine the effect of “ramping up slow”, we see an insignificant negative impact on engagement in care (−0.82, 95% CI −1.89 to 0.25). As expected, the probability of drop-out also seems to have a negative effect on engagement in care (−0.39, 95% CI −0.94 to 0.17). We further validate these results by testing with medication possession ratios calculated periodically as an alternative engagement in care metric. Our findings contradict the “Start low, go slow” adage, indicating that ramping up the dose of an antidepressant faster has a significantly positive effect on engagement in care for our population.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Comparative analysis of plasmon modes in layered Lindhard metals and strange metals

The enigmatic strange metal remains one of the central unsolved problems of 21st century science. Understanding this phase of matter requires knowledge of the momentum- and energy-resolved dynamic charge susceptibility 𝜒⁡(𝑞,𝜔), especially at finite momentum. Inelastic electron scattering (EELS), performed in either transmission or reflection geometry, is a powerful probe of 𝜒⁡(𝑞,𝜔). For the prototypical strange metal Bi 2 ⁢Sr 2 ⁢CaCu 2 ⁢O 8+𝑥 , transmission- and reflection EELS, and infrared (IR) spectroscopy agree at 𝑞∼0, all revealing a highly damped plasmon near 1 eV. At larger 𝑞, however, EELS results show unresolved discrepancies. Since IR data are highly reproducible, it is advantageous to use IR data to calculate what the expected EELS response should be at modest 𝑞. Building on prior momentum-resolved reflection geometry M-EELS work [Chen et al., Phys. Rev. B 109, 045108 (2024)], we extend this approach to transmission EELS for finite stacks of metallic layers, comparing a “textbook” Lindhard metal to a strange metal. In the Lindhard case, the low-𝑞 response is dominated by long-lived, standing wave plasmon modes arising from interlayer Coulomb coupling, with in-plane dispersions that resemble the well-known Fetter modes of layered metals. This behavior depends only on the geometry and the long-range nature of the Coulomb interaction and is largely insensitive to layer details. At larger 𝑞, the response reflects the microscopic properties of individual layers. For the strange metal, calculations based on IR data predict a highly damped plasmon with weak dispersion and no distinct surface mode. While our results match IR and M-EELS at low 𝑞, they do not reproduce any published EELS spectra at large 𝑞, highlighting unresolved discrepancies that demand further experimental investigation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Electronic and optical properties of crystalline nitrogen versus black phosphorus: A comparative first-principles study

We report crystalline black nitrogen (BN) is an allotrope of nitrogen with the black phosphorus (BP) structure recently synthesized at high pressure by two independent research groups. Here, we present a systematic study of the electronic and optical properties of BN focusing on its comparison with BP. To this end, we use the state-of-the-art quasiparticle self-consistent GW approach with vertex corrections in both the electronic and optical channels. Despite many similarities, the properties of BN are found to be considerably different. Unlike BP, BN exhibits a larger optical gap (2.5 vs 0.26 eV), making BN transparent in the visible spectral region with a highly anisotropic optical response. This difference can be primarily attributed to a considerably reduced dielectric screening in BN, leading to enhancement of the effective Coulomb interaction. Despite relatively strong Coulomb interaction, exciton formation is largely suppressed in both materials. Our analysis of the elastic properties shows exceptionally high stiffness of BN, comparable to that of diamond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Comparing theoretical predictions of radiation-free velocities of edge dislocations to molecular dynamics simulations

Transonic defect motion is of interest for high strain-rate plastic deformation as well as for crack propagation. Ever since Eshelby's 1949 prediction [J. D. Eshelby, Proc. Phys. Soc. A 62, 307 (1949)] in the isotropic limit of a “radiation-free” transonic velocity $v$ RF = $\sqrt{2}$c T , where shock waves are absent, there has been speculation about the significance of radiation-free velocities (if they truly exist) for defect mobility. Here, in this work, we argue that they do not play any significant role in dislocation dynamics in metals, based on comparing theoretical predictions of radiation-free velocities for transonic edge dislocations with molecular dynamics simulations for two face-centered cubic metals: Ag, where theory predicts radiation-free states, and Cu, where it does not.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Electronic structure, magnetic correlations, and superconducting pairing in the reduced Ruddlesden-Popper bilayer La 3 Ni 2 O 6 under pressure: Different role of d 3 z 2 - r 2 orbital compared with La 3 Ni 2 O 7

The recent discovery of superconductivity in bilayer La 3 Ni 2 O 7 (327-LNO) under pressure stimulated much interest in layered nickelates. However, superconductivity was not found in another bilayer nickelate system, La 3 Ni 2 O 6 (326-LNO), even under pressure. To understand the similarities and differences between 326-LNO and 327-LNO, using density functional theory and the random phase approximation (RPA), we systematically investigate 326-LNO under pressure. The large crystal-field splitting between the e g orbitals caused by the missing apical oxygen moves the d 3z 2 -r 2 orbital farther away from the Fermi level, implying that the d 3z 2 -r 2 orbital plays a less important role in 326-LNO than in 327-LNO. This also results in a smaller bandwidth for the d x 2 -y 2 orbital and a reduced energy gap for the bonding-antibonding splitting of the d 3z 2 -r 2 orbital in 326-LNO, as compared to 327-LNO. Moreover, the in-plane hybridization between the d x 2 -y 2 and d 3z 2 -r 2 orbitals is found to be small in 326-LNO, while it is much stronger in 327-LNO. Furthermore, the low-spin ferromagnetic state is found to be the likely ground state in 326-LNO under high pressure. The weak interlayer coupling suggests that s ± -wave pairing is unlikely in 326-LNO. The robust in-plane ferromagnetic coupling also suggests that d-wave superconductivity, which is usually caused by antiferromagnetic fluctuations of the d x 2 -y 2 orbital, is also unlikely in 326-LNO. These conclusions are supported by our many-body RPA calculations of the pairing behavior. Additionally, contrasting with the cuprates, for the bilayer cuprate HgBa 2 CaCu 2 O 6 , we find a strong self-doping effect of the d x 2 -y 2 orbital under pressure, with the charge of Cu being reduced by approximately 0.13 electrons from 0 GPa to 25 GPa. In contrast, we do not observe such a change in the electronic density in 326-LNO under pressure, establishing another important difference between the nickelates and the cuprates.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Rotational excitations in rare-earth nuclei: A comparative study within three cranking models with different mean fields and treatments of pairing correlations

High-spin rotational bands in rare-earth Er (Z = 68), Tm (Z = 69), and Yb (Z = 70) isotopes are investigated by three different nuclear models. These are (i) the cranked relativistic Hartree-Bogoliubov (CRHB) approach with approximate particle number projection by means of the Lipkin-Nogami (LN) method, (ii) the cranking covariant density functional theory (CDFT) with pairing correlations treated by a shell-model-like approach (SLAP) or the so-called particle-number conserving (PNC) method, and (iii) cranked shell model (CSM) based on the Nilsson potential with pairing correlations treated by the PNC method. A detailed comparison between these three models in the description of the ground-state rotational bands of even-even Er and Yb isotopes is performed. The similarities and differences between these models in the description of the moments of inertia, the features of band crossings, and equilibrium deformations and pairing energies of the even-even nuclei under study are discussed. These quantities are considered as a function of rotational frequency and proton and neutron numbers. The changes in the properties of the first band crossings with increasing neutron number in this mass region are investigated. On average, a comparable accuracy of the description of available experimental data is achieved in these models. However, the differences between model predictions become larger above the first band crossings. Because of the time-consuming nature of numerical calculations in the CDFT-based models, a systematic study of the rotational properties of both ground-state and excited-state bands in odd-mass Tm nuclei is carried out only by the PNC-SCM. With few exceptions, the rotational properties of experimental 1-quasiparticle and 3-quasiparticle bands in 165,167,169,171 Tm are reproduced reasonably well. As a result, the appearance of backbendings or upbendings in these nuclei is well understood from the analysis of the variations of the occupation probabilities of the single-particle states and their contributions to total angular momentum alignment with rotational frequency.

150 ≤ A ≤ 189↗