bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Numerical Solution of Heat-Conduction Problems
Authors: Emmons H. W. 
Published: December 2022

Abstract
Two- and three-dimensional steady-flow heat-conduction problems are readily solved to any degree of approximation by application of the relaxation method introduced by Southwell. Except for the simplest geometric shapes and boundary conditions, the relaxation method is far superior to analytical methods of solution in point of time required to reach a given desired accuracy. The relaxation method has the further advantages of permitting the calculator to put into the calculation all the physical intuition he may have about the problem and, at the same time, to know at each step just how seriously his solution still differs from the correct answer. By an extension of the method one-, two-, and three-dimensional transient-heat-flow problems are easily solved. For one-dimensional problems, the new method is identical to the graphical method of Schmidt.
Performance and Selection of Mechanical-Draft Cooling Towers
Authors: Lichtenstein Joseph 
Published: December 2022

Abstract
This paper indicates the need for standardization in cooling-tower practice and the adoption of a common basic theory for correlation of the vast amount of experimental data, coupled with practical experience now available. Such a theory would be invaluable in calculating performance at the guarantee point from test data taken under other conditions of service. From Merkel’s differential equation for the cooling tower, the author derives a basic dimensionless equation for calculating cooling-tower performance. A graphic method of solution of this basic equation is then given in the form of curves which have been developed by the author’s company as a result of extensive tests which are explained. It is further shown that the size of a cooling tower for a fixed set of conditions is not entirely determined by theory alone, but that economic conditions constitute the final criterion.
Nonlinear Agent-Based Dynamics: Which Metric Mitigates Polarization?
Authors: Herzog Bodo 
Published: December 2022

Abstract
This article provides a stochastic agent-based model to exhibit the role of aggregation metrics in order to mitigate polarization in a complex society. Our sociophysics model is based on interacting and nonlinear Brownian agents, which allow us to study the emergence of collective opinions. The opinion of an agent, xi(t) is a continuous positive value in an interval [0,1]. We find: (i) most agent-metrics display similar outcomes, (ii) The middle-metric and noisy-metric obtain new opinion dynamics either toward assimilation or fragmentation, and (iii) We show that a developed two-stage metric provide new insights about convergence and equilibria. In summary, our simulation demonstrates the power of institutions, which affect the emergence of collective behavior. Consequently, opinion formation in a decentralized complex society is reliant to the individual information processing and rules of collective behavior.
Beams With a Varying Cross Section in the Generalized Strain Formulation for Flexure Modeling
Authors: Dwarshuis Koen , Aarts Ronald , Ellenbroek Marcel , Brouwer Dannis 
Published: December 2022

Abstract
Flexure joints are rapidly gaining ground in precision engineering because of their predictable behavior. However, their range of motion is limited due to a stress limitation and a loss of support stiffness in deformed configurations. The support stiffness can be significantly increased by using leafsprings of which the width and thickness vary over the length of the leafspring. This paper presents formulations for two beam elements with a varying cross section that can be used for the efficient modeling of these types of leafsprings. One of these beam-formulations includes the modeling of the warping due to torsion, which is shown to be essential for accurate modeling. The 90% accuracy in stiffness results and 80% accuracy in stress results, in comparison with results of finite element analyses, are sufficient for the evaluation of concept-designs. Optimizations show that the support stiffness of two typical flexure joints can be increased by a factor of up to 4.0 keeping the same range of motion, by allowing the cross section to vary over the length of the leafspring. In these two flexure joints, 98% of this improvement can already be obtained by only varying the thickness, and keeping a constant width.
Convective Boundary Layer Flow Adjacent to an Inclined and Linearly Heated Semi-Infinite Plate
Authors: Liu Yang , Ren Sitao 
Published: December 2022

Abstract
The transient convective flow adjacent to an inclined semi-infinite plate which is heated by a linear temperature gradient is investigated with scaling analysis and direct numerical simulation (DNS) in this study. Both Pr &lt; 1 and Pr &gt; 1 fluids are considered. The initial ambient fluid is quiescent and thermally homogeneous. Important parameters characterizing the thermal boundary layer flow are thickness, characteristic velocity, and time to reach the steady stage. Scaling analysis is carried out to obtain scales for these flow parameters. Compared to previous similar studies, the obtained scale relations are more generalized and they can be utilized for different inclination angles. The derived scales are compared against the DNS results for a variety of flow parameters, e.g., Rayleigh number Ra, Prandtl number Pr, stratification factor s (s = dθw(y)/dy, where θw(y) is the local temperature at a streamwise location of y), inclination angle of the heated plate α, evolutionary time τ, and streamwise location y. The scale relations and the DNS results compare well suggesting the proposed scale laws can provide a sound description for the dynamics of the convective flow subjected to a tilted surface and a linear heating condition.
Design De-Identification of Thermal History for Collaborative Process-Defect Modeling of Directed Energy Deposition Processes
Authors: Fullington Durant , Bian Linkan , Tian Wenmeng 
Published: December 2022

Abstract
There is an urgent need for developing collaborative process-defect modeling in metal-based additive manufacturing (AM). This mainly stems from the high volume of training data needed to develop reliable machine learning models for in-situ anomaly detection. The requirements for large data are especially challenging for small-to-medium manufacturers (SMMs), for whom collecting copious amounts of data is usually cost prohibitive. The objective of this research is to develop a secured data sharing mechanism for directed energy deposition (DED) based AM without disclosing product design information, facilitating secured data aggregation for collaborative modeling. However, one major obstacle is the privacy concerns that arise from data sharing, since AM process data contain confidential design information, such as the printing path. The proposed adaptive design de-identification for additive manufacturing (ADDAM) methodology integrates AM process knowledge into an adaptive de-identification procedure to mask the printing trajectory information in metal-based AM thermal history, which otherwise discloses substantial printing path information. This adaptive approach applies a flexible data privacy level to each thermal image based on its similarity with the other images, facilitating better data utility preservation while protecting data privacy. A real-world case study was used to validate the proposed method based on the fabrication of two cylindrical parts using a DED process. These results are expressed as a Pareto optimal solution, demonstrating significant improvements in privacy gain and minimal utility loss. The proposed method can facilitate privacy improvements of up to 30% with as little as 0% losses in dataset utility after de-identification.
Comparative Life Cycle Assessment of Injection Molded and Big Area Additive Manufactured NdFeB Bonded Permanent Magnets
Authors: Kulkarni Sameer , Zhao Fu , Nlebedim Ikenna C. , Fredette Robert , Paranthaman Mariappan Parans 
Published: December 2022

Abstract
Permanent magnets are expected to play a crucial role in the realization of the clean economy. In particular, the neodymium–iron–boron (Nd2Fe14B or NdFeB) magnets, which have the highest energy density among rare earth permanent magnets, are needed for building more efficient windmill generators, electric vehicle motors, etc. Currently, near-net shape magnets can be either made through sintering and compression molding with extensive post machining or directly through injection molding. However, injection molding has a loading volume fraction limitation of 0.65 for nylon binders. A novel method of manufacturing bonded permanent magnets with loading fraction greater than 0.65 has been demonstrated using big area additive manufacturing (BAAM) printers. As energy density is directly proportional to the square of the magnet loading fraction, magnets produced using BAAM printers require less volume and magnetic material compared to that of injection molded magnets on average. A comparative life cycle assessment shows that this difference in magnetic powder consumption nearly constitutes the difference in the environmental impact categories. Even after assuming recycled magnetic input, the BAAM magnets perform better environmentally than injection molded magnets, especially in the ozone depletion category. Since BAAM printers can accommodate even higher loading fractions, at scale, BAAM printers possibly can bring about a significant decrease in rare earth mineral consumption and environmental emissions. Furthermore, single screw extrusion enables BAAM printers to have high print speeds and allow them to be economically competitive against injection molding. Therefore, BAAM printed magnets show great promise in transitioning towards the clean economy.
Design and Validation of a Steerable Port Delivery Cannula System for Laser Interstitial Thermal Therapy
Authors: Agwu Nnaoma , Leuthardt Eric , Gorlewicz Jenna 
Published: December 2022

Abstract
MRI (Magnetic Resonance Imaging) guided laser interstitial thermal therapy (LITT) is a procedure used for treating glioblastomas and epilepsy lesions in the brain. Current methods for placing LITT ablation probes use straight trajectories. This limits the treatment area, necessitating multiple passes of straight trajectories or risking untreated tumor margins. This work presents a port delivery cannula system (PDCS) to be integrated within existing surgical workflows of LITT, providing off-axis navigation to areas otherwise deemed inaccessible. The design of the PDCS is centered around a two-tube, Nitinol active cannula system, which delivers, places, and retracts a flexible, thermoplastic port along curved trajectories. We present the design of the PDCS system and validate it in free-space, phantom models, and ovine brain trials, with a specific focus on evaluating key parameters of port material characteristics. Eight commercial, biocompatible ports and five custom ports created using additive manufacturing were investigated. Results illustrate that ideal port characteristics include durometers between 85A-95A, a low coefficient of friction, and a wall thickness of approximately 20% of the overall port diameter. Our results also demonstrate that the PDCS system can achieve accuracies under 1mm in phantom models and 2mm in ovine tissue.
Development of a Computational Framework for the Evaluation of Biodegradable Cerebral Stents With Enhanced Bending Performance
Authors: Shi Weiliang , Zhang Cheng , Xie Ankun , Mitchell Kellen , Jin Yifei , Zhao Danyang 
Published: December 2022

Abstract
Cerebral aneurysm disease has extremely high mortality and morbidity, which can be efficiently treated by implanting a vascular stent. However, due to relatively poor flexibility and biodegradability, current vascular stents still cause some life-threatening complications. Thus, it is of great significance to develop new biodegradable cerebral stents (BCSs) with enhanced flexibility for improving the prognosis of cerebral aneurysm disease. In this work, a flexibility-enhanced BCS architecture has been investigated and designed. Both numerical simulation and experiments have been performed to demonstrate the potential clinical application of the proposed BCSs. First, the effects of the structural parameters on the flexibility have been analyzed by finite element simulation. Then, the mechanical properties of the proposed BCSs have been characterized via both numerical simulation and experiments and compared to those of two representative commercial stents for demonstrating the flexibility and radial stiffness of the proposed design. The knowledge from this work provides a new design methodology.
Numerical and Experimental Investigation of Streamlines for Tandem Impeller in a Centrifugal Pump
Authors: Nicola Yannick , Fensterseifer Manuel , Böhle Martin 
Published: December 2022

Abstract
Radial fluid machines with conventional impeller often lead to flow separation in the blade passage in case of high flow deflection. Tandem blades can be used to counteract this problem. Due to their properties, a new thin boundary layer forms at the rear blade profile, which benefits the deflection of the flow. The present investigation focuses on a comparison between numerical and experimental streamline patterns on the impellers blades suction side. For this purpose, a conventional impeller is compared with a tandem impeller. Furthermore, a method for creating oil painting patterns in a rotating system is presented. The numerical investigations were performed using a full model (including inlet section, impeller, volute, outlet section and impeller side gaps). A total of four operating points were examined in the range from high partial load to overload. The same operating points were run in a pump loop during the experiment. The results of the present work show that the numerically and experimentally generated streamline patterns agree well with exceptions. It could be shown that a flow separation of the blades suction side can be prevented using tandem blades.
Prediction and Validation of Flow Properties in Porous Lattice Structures
Authors: Mishra Ashreet , Korba David , Kaur Inderjot , Singh Prashant , Li Like 
Published: December 2022

Abstract
High-porosity metal foams have been extensively studied as an attractive candidate for efficient and compact heat exchanger design. With the advancements in additive manufacturing, such foams can be manufactured with controlled topology to yield highly tailorable mechanical and transport properties. In this study, a lattice Boltzmann method (LBM)-based pore-scale model is implemented to simulate the fluid flow in additively manufactured (AM) metal foams with unit cell topologies of Cube, Face Diagonal (FD)-Cube, Tetrakaidecahedron (TKD), and Octet lattices. The pressure gradient versus average velocity profiles predicted by the LBM model were validated against in-house measurements on the AM lattice samples with the same unit cell topologies. Based on the simulation results, a novel hybrid model is proposed to accurately predict the volume averaged flow properties (permeability and inertial coefficients) of the four structures. Specifically, the linear LBM (neglecting inertial forces) is first implemented to obtain the intrinsic permeability, and then the standard LBM is applied to obtain the inertial coefficient. Convenient correlations for those flow properties as a function of porosity and fiber diameter are constructed. The effects of the AM print qualities on the flow properties are also discussed. The advantages of the hybrid model compared to the polynomial fitting approach for determining flow properties are discussed and compared quantitatively. The hybrid model and presented results are valuable for flow and thermal transport evaluation when designing new metal foams for specific applications and with different materials and topologies. The presented correlations based on pore-scale simulations can also be conveniently used in volume-averaged models to predict the macroscale flow behavior in such complex structures.
Self-Triggered Model Predictive Control With Sample-and-Hold Fashion for Constrained Continuous-Time Linear Systems
Authors: He Ning , Zhang Yiwen , Ma Kai , Chen Qingqing , Li Yuxiang 
Published: December 2022

Abstract
A novel self-triggered model predictive control (STMPC) strategy for linear constrained systems with additive disturbance is presented in this paper. The actuator adopts the control input from the controller by sample-and-hold fashion. At the same time, the triggering threshold is designed to ensure the feasibility of the algorithms and the stability of the closed-loop system. Furthermore, two different ways to generate the event triggered input signal, namely, using single sample and multiple samples, are proposed and it is shown that better triggering performance can be obtained as the number of samples increases. In the last, the effectiveness and applicability of the proposed methods are verified by simulation.
Energy-Optimal Unmanned Aerial Vehicles Motion Planning and Control Based on Integrated System Physical Dynamics
Authors: Michel Nicolas , Wei Peng , Kong Zhaodan , Lin Xinfan 
Published: December 2022

Abstract
Electric vertical-take-off-and-landing multirotor aircraft has been emerging as a revolutionary transportation mode for both manned and unmanned applications, but this technology is limited by flight time and range restrictions. In this work, an energy-efficient model-based trajectory planning and feedback control framework is developed to improve the energy performance of a multirotor unmanned aerial vehicle. Target vehicle trajectories are planned by solving a formulated energy consumption optimization problem based on a system-level model, which accommodates the integrated dynamics of key vehicle subsystems. In order to implement the generated target trajectories, the framework also includes a PID feedback control architecture for real-time trajectory following. The framework is first verified under simulation, and shows an average reduction of 10.7% in energy consumption over a range of typical hover-to-hover operations, compared to the commonly used baseline flight control architecture. Through model-based analysis, key relationships that contribute to the improvements are identified and analyzed. These results demonstrate the importance of considering and coordinating all relevant system dynamics for efficient and holistic trajectory planning and control, which is absent in existing literature. The framework also demonstrates similar performance improvement under experimental validation, with an average energy reduction of 10.2% over the baseline controller despite the presence of significant real-world disturbances including wind effect.
Clinical risk factors for testicular torsion and a warning against falsely reassuring ultrasound scans: a 10-year single-centre experience
Authors: Lukosiute-Urboniene Ausra , Nekrosius Deividas , Dekeryte Inga , Kilda Arturas , Malcius Dalius 
Published: December 2022

BackgroundWe sought to determine which demographic, clinical and ultrasonography characteristics are predictive of testicular torsion (TT) and to determine factors associated with time to treatment.MethodsWe retrospectively reviewed all medical records of patients (0–17 years) with acute scrotal syndrome (ASS) who were treated in our hospital in Lithuania between 2011 and 2020. We extracted patients’ demographic data, in-hospital time intervals, clinical, US and surgical findings. TT was determined at surgery or clinically after manual detorsion. Test characteristics of demographic, clinical and US findings for the diagnosis of TT versus other causes of ASS were determined. We performed a multivariate analysis to identify independent clinical predictors of torsion, and factors associated with surgical delay.ResultsA search of medical records yielded 555 cases: 196 (35%) patients with TT and 359 (65%) patients with other ASS causes. Multivariate logistic regression analysis showed that age between 13 and 17 years (OR 8.39; 95% CI 5.12 to 13.76), duration of symptoms <7 hours (OR 3.41; 95% CI 2.03 to 5.72), palpated hard testis (OR 4.65; 95% CI 2.02 to 10.67), scrotal swelling (OR 2.37; 95% CI 1.31 to 4.30), nausea/vomiting (OR 4.37; 95% CI 2.03 to 9.43), abdominal pain (OR 2.38; 95% CI 1.27 to 4.45) were independent clinical predictors of TT. No testicular blood flow in Doppler US had a specificity of 98.2% and a positive predictive value of 94.6%. However, 75 (41.7%) patients with TT had normal testicular blood flow, yielding low sensitivity (58.3%) and negative predictive value of 81.3% for this US finding. In-hospital waiting time for surgery was longer in patients with TT with normal testicular blood flow by USS (195 min) compared with no blood flow (123 min), p<0.01. Higher orchiectomy rates were associated with longer duration of symptoms (p<0.001) and longer waiting time for USS (p=0.029) but not with false-negative US.ConclusionsPubertal age, symptoms duration of <7 hours, nausea/vomiting, palpated hard testis, abdominal pain and scrotal swelling are predictive factors for TT. Time lost between symptom onset and seeking medical care, and between arrival and US are associated with the need for orchiectomy. Preserved blood flow in USS does not rule out TT and may contribute to delays to surgery.
Algorithm 1034: An Accelerated Algorithm to Compute the

Q
n

Robust Statistic, with Corrections to Constants
Authors: Fahmy Thierry 
Published: December 2022

The robust scale estimator

Q
n

developed by Croux and Rousseeuw [
3
], for the computation of which they provided a deterministic algorithm, has proven to be very useful in several domains including in quality management and time series analysis. It has interesting mathematical (50% breakdown, 82% Asymptotic Relative Efficiency) and computing (
O(nlogn)
time,
O
(
n
) space) properties. While working on a faster algorithm to compute

Q
n

, we have discovered an error in the computation of the
d
constant, and as a consequence in the

d
n

constants that are used to scale the statistic for consistency with the variance of a normal sample. These errors have been reproduced in several articles including in the International Standard Organisation 13,528 [
12
] document. In this article, we fix the errors and present a new approach, which includes a new algorithm, allowing computations to run 1.3 to 4.5 times faster when
n
grows from 10 to 100,000.
PRADA: Practical Black-box Adversarial Attacks against Neural Ranking Models
Authors: Wu Chen , Zhang Ruqing , Guo Jiafeng , De Rijke Maarten , Fan Yixing , Cheng Xueqi 
Published: December 2022

Neural ranking models (NRMs) have shown remarkable success in recent years, especially with pre-trained language models. However, deep neural models are notorious for their vulnerability to adversarial examples. Adversarial attacks may become a new type of web spamming technique given our increased reliance on neural information retrieval models. Therefore, it is important to study potential adversarial attacks to identify vulnerabilities of NRMs before they are deployed.In this article, we introduce the Word Substitution Ranking Attack (WSRA) task against NRMs, which aims at promoting a target document in rankings by adding adversarial perturbations to its text. We focus on the decision-based black-box attack setting, where the attackers cannot directly get access to the model information, but can only query the target model to obtain the rank positions of the partial retrieved list. This attack setting is realistic in real-world search engines. We propose a novel Pseudo Relevance-based ADversarial ranking Attack method (PRADA) that learns a surrogate model based on Pseudo Relevance Feedback (PRF) to generate gradients for finding the adversarial perturbations.Experiments on two web search benchmark datasets show that PRADA can outperform existing attack strategies and successfully fool the NRM with small indiscernible perturbations of text.