Torque magnetometry study of the spin reorientation transition and temperature-dependent magnetocrystalline anisotropy in NdCo5

We present the results of torque magnetometry and magnetic susceptibility measurements to study in detail the spin reorientation transition (SRT) and magnetic anisotropy in the permanent magnet NdCo5. We further show simulations of the measurements using first-principles calculations based on density-functional theory and the disordered local moment picture of magnetism at finite temperatures. The good agreement between theory and experimental data leads to a detailed description of the physics underpinning the SRT. In particular we are able to resolve the magnetization of, and to reveal a canting between, the Nd and Co sublattices. The torque measurements carried out in the ac and ab planes near the easy direction allow us to estimate the anisotropy constants, K 1, K 2 and K 4 and their temperature dependences. Torque curves, τ(γ) recorded by varying the direction of a constant magnetic field in the crystallographic ac plane show a reversal in the polarity as the temperature is changed across the SRT (240 < T < 285 K). Within this domain, τ(γ) exhibits unusual features different to those observed above and below the transition. The single crystals of NdCo5 were grown using the optical floating zone technique

Tunability of the spin reorientation transitions with pressure in NdCo5

We present pressure-dependent magnetization measurements carried out in the domain of the spin reorientation transitions (SRTs) of a NdCo5 single crystal. The application of a hydrostatic pressure leads to a shift in the SRTs to higher temperatures. This shift is found to be very sensitive to pressure, with the SRT temperatures increasing at a rate of ≈17 K/GPa. To explain the experimental results, we have also performed first-principles calculations of the SRT temperatures for different applied strains, which corroborate the experimental findings. The calculations attribute the pressure dependence of the SRTs to a faster weakening of the Co contribution to the magnetocrystalline anisotropy with pressure compared to the Nd contribution

The Subpulse Modulation Properties of Pulsars and its Frequency Dependence

A large sample of about two hundred pulsars have been observed to study their subpulse modulation at an observing wavelength of (when achievable) both 21 and 92 cm using the Westerbork Synthesis Radio Telescope. For 57 pulsars drifting subpulses are discovered for the first time and are confirmed for many others. This leads to the conclusion that it could well be that the drifting subpulse mechanism is an intrinsic property of the emission mechanism itself, although for some pulsars it is difficult or impossible to detect. It appears that the youngest pulsars have the most disordered subpulses and the subpulses become more and more organized into drifting subpulses as the pulsar ages. Drifting subpulses are in general found at both frequencies and the measured values of P3 at the two frequencies are highly correlated, showing the broadband nature of this phenomenon. Also the modulation indices measured at the two frequencies are clearly correlated, although at 92 cm they are on average possibly higher. The correlations with the modulation indices are argued to be consistent with the picture in which the radio emission is composed out of a drifting subpulse signal plus a quasi-steady signal which becomes, on average, stronger at high observing frequencies. There is no obvious correlation found between P3 and the pulsar age (or any other pulsar parameter) contrary to reports in the past.Comment: Proceedings of the 40 Years of Pulsars: Millisecond Pulsars, Magnetars and More conference in Montrea

Dynamical heterogeneity in a glass forming ideal gas

We conduct a numerical study of the dynamical behavior of a system of three-dimensional crosses, particles that consist of three mutually perpendicular line segments rigidly joined at their midpoints. In an earlier study [W. van Ketel et al., Phys. Rev. Lett. 94, 135703 (2005)] we showed that this model has the structural properties of an ideal gas, yet the dynamical properties of a strong glass former. In the present paper we report an extensive study of the dynamical heterogeneities that appear in this system in the regime where glassy behavior sets in. On the one hand, we find that the propensity of a particle to diffuse is determined by the structure of its local environment. The local density around mobile particles is significantly less than the average density, but there is little clustering of mobile particles, and the clusters observed tend to be small. On the other hand, dynamical susceptibility results indicate that a large dynamical length scale develops even at moderate densities. This suggests that propensity and other mobility measures are an incomplete measure of dynamical length scales in this system.Comment: 11 pages, 7 figure

Floodplain Restoration and Its Effects on Summer Water Temperature and Macroinvertebrates in Whychus Creek, Oregon (USA)

Stream restoration is a proposed climate adaptation tool; however, outcomes of floodplain restoration on stream temperature have been debated. Despite a growing number of studies that investigated water temperature in restored streams, few have quantified temperature variations in new habitat types created by restored hydrogeomorphic processes to explore the effects on aquatic macroinvertebrates. We evaluated the hypotheses: (1) restoration increases habitat diversity, (2) habitat diversity increases water temperature variability, and (3) restoration increases the diversity of macroinvertebrate assemblage and temperature associations. In August 2021, we collected environmental data to describe the aquatic habitats, water temperature and quality (continuous and discrete), and macroinvertebrates in 40 riffle, pool, and off-channel sites in a stream being restored, Whychus Creek, Oregon, USA. Our study is a site comparison of three reaches—one restored in 2012, another restored in 2016, and an unrestored (control) that will soon undergo restoration. Evaluations of the hypotheses show: (1) Habitat diversity in restored reaches is effectively three types of aquatic habitats versus only one in the control (riffles), (2) water temperature variability in habitats created by restoration (off-channel) is high and low, and suggest a range of hyporheic connectivity and flow paths are present, and (3) restoration created a different macroinvertebrate assemblage, with 16 additional taxa in off-channel habitats, and the range in macroinvertebrate thermal optima is approximately doubled when off-channel macroinvertebrate thermal optima are accounted for. Our results support the idea that floodplain restoration creates more diverse thermal conditions and different macroinvertebrate communities in restored stream reaches

Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory

It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions

Structural and magnetic properties of GdCo5−xNix

GdCo5 may be considered as two sublattices—one of Gd and one of Co—whose magnetizations are in antiparallel alignment, forming a ferrimagnet. Substitution of nickel in the cobalt sublattice of GdCo5 has been investigated to gain insight into how the magnetic properties of this prototype rare earth/transition-metal magnet are affected by changes in the transition-metal sublattice. Polycrystalline samples of GdCo5-xNix for 0 ≤ x ≤ 5 were synthesized by arc melting. Structural characterization was carried out by powder x-ray diffraction and optical and scanning electron microscope imagings of metallographic slides, the latter revealing a low concentration of Gd2(Co,Ni)7 lamellae for x ≤ 2.5. Compensation—i.e., the cancellation of the opposing Gd and transition-metal moments—is observed for 1< x < 3 at a temperature which increases with Ni content; for larger x , no compensation is observed below 360 K. A peak in the coercivity is seen at x ≈ 1 at 10 K coinciding with a minimum in the saturation magnetization. Density-functional theory calculations within the disordered local moment picture reproduce the dependence of the magnetization on Ni content and temperature. The calculations also show a peak in the magnetocrystalline anisotropy at similar Ni concentrations to the experimentally observed coercivity maximum

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made