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Fu, B.

Publications and source records attributed to Fu, B..

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measurement of inclusive $J/ψ$ production in Au+Au collisions at $\sqrt{s_{\textrm{NN}}}$ = 54.4 GeV at STAR

This article presents measurements of inclusive J/ψ production at midrapidity (|y| < 1.0) in Au+Au collisions at $\sqrt{s_{\textrm{NN}}}$ = 54.4 GeV with the STAR detector at the Relativistic Heavy Ion Collider. A suppression of the J/ψ yield, quantified using the nuclear modification factors (R AA , R CP ), is observed with respect to the scaled production p + p in collisions. The dependence of R AA on collision centrality and J/ψ transverse momentum is measured with improved precision compared to previous measurements at 39 and 62.4 GeV, while the centrality dependence of R CP is measured and compared to the same results at 39, 62.4, and 200 GeV. In central collisions, no significant collision energy dependence of R AA is found within uncertainties for collision energies between 17.3 and 200 GeV. Two transport model calculations that include dissociation and regeneration contributions are consistent with the experimental results within uncertainties. Although no significant collision energy dependence of the J/ψ suppression in high energy heavy-ion collisions up to $\sqrt{s_{\textrm{NN}}}$ = 200 GeV is observed within uncertainties, the newly measured results at 54.4 GeV Au+Au collisions provide additional constraints on theoretical calculations of the hot medium evolution and cold nuclear matter effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Probing late-stage hadronic interactions at high baryon density via $K^{⁎0}$ production in the RHIC beam energy scan program

A precision measurement of the $K^{⁎0}$ meson yield is reported in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7, 11.5, 14.6, 19.6, and 27 GeV using the high-statistics data sample collected by the STAR experiment during the Beam Energy Scan II (BES-II) program at RHIC. The transeverse momentum (p T )-integrated yield ratios $\large{(}K^{⁎0} + \overline{K^{⁎0}}\large{)}/(K^+ + K^{-})$ in central collisions show a suppression relative to peripheral collisions at the (1.7–3.6) σ level, while a thermal model without final-stage rescattering overpredicts this ratio with a deviation of (6.9–8.2) σ. These results indicate a loss of the measured $K^{⁎0}$ signal in central collisions due to re-scattering of its hadronic decay products in the hadronic phase. The p T -integrated yield of charged kaons exhibits an approximate scaling with charged-particle multiplicity, independent of collision energy and system size. A similar trend is observed for the short-lived $K^{⁎0}$ resonance, although significant deviations emerge at lower energies. At BES energies, the $K^{⁎0}/K$ ratio shows stronger suppression than at the highest RHIC and LHC energies within a given multiplicity bin, particularly in central and mid-central collisions. This behavior is consistent with changes in the effective hadronic interaction cross section and is supported by transport model calculations, which indicate dominant meson–baryon interactions at lower energies and meson–meson interactions at higher energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Measurement of kaon directed flow in Au+Au collisions in the high baryon density region

Rapidity-odd directed flow v 1 measurements are presented for $K^±$ and $K^0_S$ in Au + Au collisions for $\sqrt{s_{NN}}$ from 3.0 to 3.9 GeV with the STAR experiment. For comparison, v 1 of π ± , protons, and Λ from the same collisions are also discussed. The mid-rapidity v 1 slope dv 1 /dy| y=0 for protons and Λ is positive in these collisions. On the other hand, v 1 slope of kaons exhibits a strong dependence: negative at p T < 0.6 GeV/c and positive at higher p T . A similar p T dependence is also evident for the v 1 slope of charged pions. Compared to the spectator-removed calculations in Au+Au collisions at $\sqrt{s_{NN}}$ = 3.0–3.9 GeV, the JAM model demonstrates a pronounced shift of the v 1 slopes of mesons towards the negative direction. It suggests that the shadowing effect of the spectators plays an important role in the observed kaon anti-flow at low p T in the high baryon density region of non-central collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1996

Processing of nutritious, safe and acceptable foods from CELSS candidate crops

A controlled ecological life-support system (CELSS) is required to sustain life for long-duration space missions. The challenge is preparing a wide variety of tasty, familiar, and nutritious foods from CELSS candidate crops under space environmental conditions. Conventional food processing technologies will have to be modified to adapt to the space environment. Extrusion is one of the processes being examined as a means of converting raw plant biomass into familiar foods. A nutrition-improved pasta has been developed using cowpea as a replacement for a portion of the durum semolina. A freeze-drying system that simulates the space conditions has also been developed. Other technologies that would fulfill the requirements of a CELSS will also be addressed.

NASA Discipline Number 93-10↗
NASA NTRS1994

Conditions and constraints of food processing in space

Requirements and constraints of food processing in space include a balanced diet, food variety, stability for storage, hardware weight and volume, plant performance, build-up of microorganisms, and waste processing. Lunar, Martian, and space station environmental conditions include variations in atmosphere, day length, temperature, gravity, magnetic field, and radiation environment. Weightlessness affects fluid behavior, heat transfer, and mass transfer. Concerns about microbial behavior include survival on Martian and lunar surfaces and in enclosed environments. Many present technologies can be adapted to meet space conditions.

NASA Discipline Life Support Systems↗
NASA NTRS1993

Minimizing distortion in truss structures -- a Hopfield network solution

Distortions in truss structures can result from random errors in elemental lengths that are typical of a manufacturing process. These distortions may be minimized by an optimal selection of elements from those available for placement between the prescribed nodes -- a combinatorial optimization problem requiring significant investment of computational resource for all but the smallest problems. The present paper describes a formulation in which near-optimal element assignments are obtained as minimum energy, stable states, of an analogous Hopfield neural network. This requires mapping of the optimization problem into an energy function of the appropriate Lyapunov form. The computational architecture is ideally suited to a parallel processor implementation and offers significant savings in computational effort. A numerical implementation of the approach is discussed with reference to planar truss problems.

Fu, B.↗
NASA NTRS1993

Self-organization in neural networks - Applications in structural optimization

The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.

Hajela, Prabhat↗
NASA NTRS1992

Minimizing distortion in truss structures - A Hopfield network solution

Distortions in truss structures can result from random errors in element lengths that are typical of a manufacturing process. These distortions may be minimized by an optimal selection of elements from those available for placement between the prescribed nodes - a combinatorial optimization problem requiring significant investment of computational resource for all but the smallest problems. The present paper describes a formulation in which near-optimal element assignments are obtained as minimum-energy stable states, of an analogous Hopfield neural network. This requires mapping of the optimization problem into an energy function of the appropriate Liapunov form. The computational architecture is ideally suited to a parallel processor implementation and offers significant savings in computational effort. A numerical implementation of the approach is discussed with reference to planar truss problems.

Fu, B.↗