Physical Part Research Articles

6G Networks Orientation by Quantum Mechanics

Quantum mechanics is a part of physics that studies the interactions of matter, light, and particles at the atomic and subatomic levels. Since its initial concepts in the early 1900s built upon extensive research of Nobel laureates such as Max Planck, Niels Bohr, Albert Einstein, and Richard Feynman, amongst others to the first proposed quantum computers by Paul Benioff in 1980, the concept of quantum technologies has evolved. Two central studies derived from quantum mechanics that can support and revolutionize future wireless technologies are quantum computers and quantum communications. The investigation for building the next generation of wireless networks has begun. Therefore, many technological opportunities for applying innovative solutions and advanced concepts are on the table as an option to unlock the full potential of 6G for providing an intelligent, superfast, and secure network. Having said that, quantum mechanics come into play to offer a breakthrough opportunity that will change the world since the popularization of the Internet, and it will propel 6G use cases to be remarkably successful, but only if quantum physics can be engineered and converged into the forementioned quantum technologies to support the achievement of Society 5.0. Therefore, overcoming the quantum challenges, 6G can benefit in many ways. One of them is Quantum computing (QC) that will surpass the computational capabilities of classic computers limited by binary transactions known as bits to resolve future challenges using quantum states to process information in quantum bits (Qubits). Correspondingly, quantum computing will merge with Artificial Intelligence (AI) to create a new model known as Quantum Machine Learning (QML) to deal with the exponential growth of Big Data faster than any existing computational model. In Addition, quantum communications will deliver a safer network, utilizing Quantum Key Distribution (QKD) and inaugurate the next generation of the Internet, much safer for all. Thus, this paper presents a holistic overview of Quantum as a service (QaaS) as a future deployment in the 6G architecture, but only if quantum technologies can be mastered in the next upcoming years. Most likely that QaaS will become available for commercial purposes by the hyperscalers, the ones able to cope with the total cost of ownership (TCO) of these state of art technologies. This paper is divided by an introduction that summarizes the foundation of quantum mechanics, its laws, and the researchers’ pioneers responsible for setting the principles used to create the next generation of quantum technologies. In Section 2, there is a presentation of the core parts of quantum physics used to create quantum computers and quantum communications services, which includes the technological challenges to mature these technologies. Finally, in Section 3, the conclusions are presented.

A Short History of the Development of Space Physics Based on Studies of Geomagnetic Storms

Space physics is one of the rapidly developing scientific fields, covering space from the sun to a distance of about 100 times between the sun and the earth, the region called the heliosphere. It includes parts of solar physics, geomagnetism (a study of geomagnetic storms), ionospheric physics, auroral physics, cosmic ray physics and planetary physics. The rapid progress in space physics owes a long history of debates and controversies among these sub-fields, as well as the advent of satellites and space probs, which began during the 1960s. A study of geomagnetic storms has an interesting development preceding space physics, so that it may be worthwhile to study history of space physics by following the development of the history of geomagnetic storms. The author has joined in space physics in its earliest days.

Dual tapered optical fiber for simultaneous detection of curvature and strain

We present a study of simultaneous detection of curvature and strain in optical fiber. This contains a micro tapered section and a nano tapered section. The transmission spectrum shows interference of multiple modes, and the frequency of the modulation can be used to distinguish and monitor specific physical parts of the fiber structure. The curvature detection is achieved using one specific modulation frequency component; this component shows an intensity modulation with a sensitivity of 0.26 dB/m−1. The strain information is extracted by applying a phase analysis over a second spatial frequency component; this analysis shows a sensitivity close to 8 mrad/με. The strain phase analysis exhibits a linear response, and the intensity curvature data indicates an exponential model. The proposed signal analysis can be employed for simultaneous detection in optical fiber interferometric sensors.

Visualizing Standardized Model-Based Design and Inspection Data in Augmented Reality

Abstract Augmented reality (AR) has already helped manufacturers realize value across a variety of domains, including assistance in maintenance, process monitoring, and product assembly. However, coordinating traditional engineering data representations into AR systems without loss of context and information remains a challenge. A major barrier is the lack of interoperability between manufacturing-specific data models and AR-capable data representations. In response, we present a pipeline for porting standards-based design and inspection data into an AR scene. As a result, product manufacturing information with three-dimensional (3D) model data and corresponding inspection results are successfully overlaid onto a physical part. We demonstrate our pipeline by interacting with annotated parts while continuously tracking their pose and orientation. We then validate the pipeline by testing against six fully toleranced design models, accompanied by idealized inspection results. Our work (1) provides insight on how to address fundamental issues related to interoperability between domain-specific models and AR systems and (2) establishes an open software pipeline from which others can implement and further develop.

Momentum boundary-layer characterisation from a pulsed impinging jet

The development of the unsteady boundary layer produced from an impinging jet with a temporal puslation forms part of the complex flow physics occurring within an internal combustion engine and its characterisation is crucial for improved modelling with lower-fidelity tools. The momentum boundary layer prediction of these flows currently relies on wall-modelling based on the logarithmic law of the wall for equilibrium zero pressure gradient boundary layers. However, it is not fully understood how these non-equilibrium boundary layers evolve and whether the reliance on the law of the wall is justified for modelling such flows. Thus, in this paper, we attempt to characterise the momentum boundary layer developing from a pulsed impinging jet through the use of highly-resolved large eddy simulations of a canonical setup. The simulations are conducted for three peak jet Reynolds numbers of 10,000, 20,000 and 50,000, achieved at the peak of the temporal pulse. The resulting boundary layer produced by the jet impingement is examined for the mean flow, the scaling of the outer-layer and the boundary layer parameters, such as the boundary layer thickness, the friction Reynolds number and the wall-scaled profiles. The effect of the jet Reynolds number on the different parameters is also evaluated statistically as well as temporally. The results show that the boundary layer’s development is highly unsteady, even statistically, with a large variation in the friction Reynolds number over the statistical sampling period. However, most of the values were found to be lower than the values seen for turbulent boundary layers. This leads to an at least 40% overprediction in the wall-scaled velocity when using the equilibrium law of the wall for modelling these boundary layers. The predictions of the wall-friction using the equilibrium law of the wall and select turbulence models was also tested and it was found that the latter could be useful as a recourse to the near-wall modelling of these flows.

Multiresolution surface blending for detail reconstruction

While performing mechanical reverse engineering, 3D reconstruction processes often encounter difficulties capturing small, highly localized surface information. This can be the case if a physical part is 3D scanned for life-cycle management or robust design purposes, with interest in corroded areas or scratched coatings. The limitation partly is due to insufficient automated frameworks for handling – localized – surface information during the reverse engineering pipeline. We have developed a tool for blending surface patches with arbitrary irregularities, into a base body that can resemble a CAD design. The resulting routine preserves the shape of the transferred features and relies on the user only to set some positional references and parameter adjustments for partitioning the surface features.

The evolution of synthetic receptor systems.

Receptors enable cells to detect, process and respond to information about their environments. Over the past two decades, synthetic biologists have repurposed physical parts and concepts from natural receptors to engineer synthetic receptors. These technologies implement customized sense-and-respond programs that link a cell's interaction with extracellular and intracellular cues to user-defined responses. When combined with tools for information processing, these advances enable programming of sophisticated customized functions. In recent years, the library of synthetic receptors and their capabilities has substantially evolved-a term we employ here to mean systematic improvement and expansion. Here, we survey the existing mammalian synthetic biology toolkit of protein-based receptors and signal-processing components, highlighting efforts to evolve and integrate some of the foundational synthetic receptor systems. We then propose a generalized strategy for engineering and improving receptor systems to meet defined functional objectives called a 'metric-enabled approach for synthetic receptor engineering' (MEASRE).

Symmetries as Humean Metalaws

AbstractSymmetry principles are a central part of contemporary physics, yet there has been surprisingly little metaphysical work done on them. This article develops the Wignerian treatment of symmetries as higher-order laws—metalaws—within a Humean framework of lawhood. Lange has raised two obstacles to Humean metalaws, and the article shows that the account has the resources available to respond to both. It is argued that this framework for Humean metalaws stands as an example of naturalistic metaphysics, able to bring Humeanism into contact with the practice of actual science without giving up on the central denial of necessary connections.

Planck Speed: the Missing Speed of Physics? Absolute Still Without Breaking Lorentz Symmetry!


 
 
 Today, the speed of light is one of the cornerstones of modern physics. It is the maximum speed limit for transferring information, and plays a very central role in relativity theory. It also seems to be the same as the assumed and measured speed of gravity (gravitons and/or gravitational waves). We are not questioning the speed of light, as we indeed think it is the maximum speed limit and that it is identical to the speed ofgravity, but we also think photons lead us to a second speed limit, which we will term the Planck speed. Photon-photon collisions are part of modern physics, but what is not discussed is the speed of two photons during the very moment of a photon-photon collision. How can photons move during a collision? Or, assumea photon is reflected by a mirror; to do so it must collide with the building blocks of the mirror, yet how can it be moving during the very collision point? Also, modern physics assumes mass can be created in a photon-photon collision. We suggest this mass is the Planck mass particle and that it only lasts one Planck time, so when two photons collide, we will claim they must stand still for the direct observer. That is, we suggest thatthe speed of the Planck mass particle is always zero, but that this zero-velocity can only last for one Planck time. That it only lasts one Planck time means it will not break with the relativity principle or Lorenz symmetry, or at least what we can call weak Lorentz symmetry. We will show that the missing Plank mass particle is the very collision point between two photons, and that this is fully in line with predictions in other researchers’ findings in relation to the possible photon mass. This new view seems to solve the missing mass-gap, and seems able to unify gravity with quantum mechanics. This again seems to unify photons with mass, because one of the long-outstanding questions in physics is whether photons have mass or not. In addition, we showhow to find, in a very simple way directly from gravitational observations, lp/tp= cg = c, which is the upper speed limit (the speed of light and gravity) independent of any knowledge of G or ~ or c.
 
 

The Grotesque World in The Heart is a Lonely Hunter

This article is going to explore the reasons leading the figures grotesque and the way out of such world, with the help of Bakhtin’s theory of grotesque realism, via linking the duality of physical part with the grotesque to analyze the three main characters’ physical characteristics, social relationships and mental world. Singer, Mick and Biff are the distinct characters in Carson McCullers’s novel The Heart is a Lonely Hunter. Their lives are shot through with frustration and discouragement and the intense privacy of their inner lives gives the reader the impression that they are isolated, lonely beings. They try to build connections with others but eventually they fail. The following are the reasons: Firstly, they cannot identify themselves with the majority due to their physical problems, which further lead to their mental crisis. Secondly, they are alienated from the majority in society while they communicate with the ones who cannot end their isolation, which enforces their alienation. Finally, loneliness grips them so powerfully that they cannot come out of their grotesque dreaming world centering on the truth or idea or purpose they have created for themselves. Therefore the way out is to experience the social reality, to express ideas, share care and love with others. Through the interpretation of this novel, the point of this article is to explain the reasons and the ways out of alienation, the keyword in the grotesque world.

A diagrammatic view of differential equations in physics

<abstract><p>Presenting systems of differential equations in the form of diagrams has become common in certain parts of physics, especially electromagnetism and computational physics. In this work, we aim to put such use of diagrams on a firm mathematical footing, while also systematizing a broadly applicable framework to reason formally about systems of equations and their solutions. Our main mathematical tools are category-theoretic diagrams, which are well known, and morphisms between diagrams, which have been less appreciated. As an application of the diagrammatic framework, we show how complex, multiphysical systems can be modularly constructed from basic physical principles. A wealth of examples, drawn from electromagnetism, transport phenomena, fluid mechanics, and other fields, is included.</p></abstract>

Fraud Detection in Supply Chain with Machine Learning

A variety of fraud in Supply Chains may be detected either in physical parts or in cyber data. We use supervised machine learning to detect various fraud and misinformation in supply chains. The study is based on a car manufacturer concerned with increasing fraud, ranging from fraudulent invoices to inflated prices. Big data is provided for pattern recognition. A macro-level code is presented with actual algorithms developed in Python. The research is continuing, while the current work is presented with promising results.

Constrained systems, generalized Hamilton-Jacobi actions, and quantization

<p style='text-indent:20px;'>Mechanical systems (i.e., one-dimensional field theories) with constraints are the focus of this paper. In the classical theory, systems with infinite-dimensional targets are considered as well (this then encompasses also higher-dimensional field theories in the hamiltonian formalism). The properties of the Hamilton–Jacobi (HJ) action are described in details and several examples are explicitly computed (including nonabelian Chern–Simons theory, where the HJ action turns out to be the gauged Wess–Zumino–Witten action). Perturbative quantization, limited in this note to finite-dimensional targets, is performed in the framework of the Batalin–Vilkovisky (BV) formalism in the bulk and of the Batalin–Fradkin–Vilkovisky (BFV) formalism at the endpoints. As a sanity check of the method, it is proved that the semiclassical contribution of the physical part of the evolution operator is still given by the HJ action. Several examples are computed explicitly. In particular, it is shown that the toy model for nonabelian Chern–Simons theory and the toy model for 7D Chern–Simons theory with nonlinear Hitchin polarization do not have quantum corrections in the physical part (the extension of these results to the actual cases is discussed in the companion paper [<xref ref-type="bibr" rid="b21">21</xref>]). Background material for both the classical part (symplectic geometry, generalized generating functions, HJ actions, and the extension of these concepts to infinite-dimensional manifolds) and the quantum part (BV-BFV formalism) is provided.</p>

Scalable algorithms for physics-informed neural and graph networks

Abstract Physics-informed machine learning (PIML) has emerged as a promising new approach for simulating complex physical and biological systems that are governed by complex multiscale processes for which some data are also available. In some instances, the objective is to discover part of the hidden physics from the available data, and PIML has been shown to be particularly effective for such problems for which conventional methods may fail. Unlike commercial machine learning where training of deep neural networks requires big data, in PIML big data are not available. Instead, we can train such networks from additional information obtained by employing the physical laws and evaluating them at random points in the space–time domain. Such PIML integrates multimodality and multifidelity data with mathematical models, and implements them using neural networks or graph networks. Here, we review some of the prevailing trends in embedding physics into machine learning, using physics-informed neural networks (PINNs) based primarily on feed-forward neural networks and automatic differentiation. For more complex systems or systems of systems and unstructured data, graph neural networks (GNNs) present some distinct advantages, and here we review how physics-informed learning can be accomplished with GNNs based on graph exterior calculus to construct differential operators; we refer to these architectures as physics-informed graph networks (PIGNs). We present representative examples for both forward and inverse problems and discuss what advances are needed to scale up PINNs, PIGNs and more broadly GNNs for large-scale engineering problems.

Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges

The number of disasters has increased over the past decade where these calamities significantly affect the functionality of communication networks. In the context of 6G, airborne and spaceborne networks offer hope in disaster recovery to serve the underserved and to be resilient in calamities. Therefore, our paper reviews the state-of-the-art literature on post-disaster wireless communication networks and provides insights for the future establishment of such networks. In particular, we first give an overview of the works investigating the general procedures and strategies for facing any large-scale disaster. Then, we present technological solutions for post-disaster communications, such as the recovery of the terrestrial infrastructure, installing aerial networks, and using spaceborne networks. Afterwards, we shed light on the technological aspects of post-disaster networks, primarily the physical and networking issues. We present the literature on channel modeling, coverage and capacity, radio resource management, localization, and energy efficiency in the physical layer part, and discuss the integrated space-air-ground architectures, routing, delay-tolerant/software-defined networks, and edge computing in the networking layer part. This paper also includes interesting simulation results which can provide practical guidelines about the deployment of ad hoc network architectures in emergency scenarios. Finally, we present several promising research directions, namely backhauling, cache-enabled and intelligent reflective surface-enabled networks, placement optimization of aerial base stations (ABSs), and the mobility-related aspects that come into play when deploying aerial networks, such as planning their trajectories and the consequent handovers (HOs).

Potential Simplification of Charge and the Coulomb Force without Affecting Predictions

We are taking a deeper look at charge and the Coulomb force and other electric properties. There is an embedded 10-7 in the Coulomb constant that we will claim is “only” needed to cancel out an embedded 107 in the charge squared. We suggest three alternatives to redefine the charge and the Coulomb constant that give considerable simplification. The Coulomb constant is not needed as a separate constant as, in the new suggested framework, it can be replaced with simply the speed of light without affecting predicted output values. We also point out potential issues with the 2019 redefinition of the Coulomb constant and elementary charge. This is not meant conclusive but to open up for further discussion on how one potential can simplify parts of physics.

Towards a Holistic Framework for Digital Twins of Human-Machine Systems

This article goes back to the origin of Digital Twin (DT) concepts, contextualizes their emergence and highlights their main key points. Models of DT are discussed with regard to nine criteria: physical asset, model, communication, service, data, product, autonomy, environment, and human. Criteria like autonomy, environment and human are rarely studied in terms of shared control between humans and machines or in terms of user surroundings integration while Human-Centered System Design approaches exist. Few of models studied consider humans as a physical part of DT. Similarly to a Machine Digital Twin, it is proposed to realized a Human Digital Twin for modelling the human part of Human-Machine Systems (HMS). Therefore, design guidelines, solutions and a new framework are proposed to set the pace for a new generation of Digital Twins.

Numerical Treatment of Boundary Conditions to Reduce High-Frequency Artifacts in Simulations of Distributed-Feedback Lasers

High-frequency artifacts may occur when the coupled-mode equations describing distributed-feedback lasers are solved by a variety of numerical methods, such as method-of-characteristics schemes and the split-step method. We propose a simple technique to suppress this artifact. Its idea is to modify the numerical implementation of the boundary conditions to promote the leakage of highest-frequency modes out of the medium. At the same time, this implementation only minimally affects the physical part of the solution. We demonstrate the effectiveness of this technique for first- and second-order schemes.

Predicting the extent to which excess lipid is deposited in the physical components of a broiler when dietary protein content is reduced

Context The weight of each of the physical parts of the body of broilers, predicted using their allometric relationship with feather-free body protein, differs with the level of dietary protein offered. Aims The objective of this study was to account for the excess lipid that is deposited differentially in the physical parts of the body of broilers when dietary protein content is decreased. Methods In total, 2496 day-old Cobb 500® and Ross 308® broilers, equally divided between males and females, were used in a 56-day feeding trial. The experimental design used was a response experiment with six balanced protein concentrations (0.60, 0.70, 0.85, 1.00, 1.15 and 1.30 of the recommendation), with two factors (males and females) and two strains (Cobb and Ross). On Days 14, 28, 42 and 56 post-hatch, eight broilers from each feed × sex × strain combination were euthanised and partitioned into breast, legs, wings, and remainder. Each component was weighed and subsequentially analysed for water, protein and lipid. Allometric equations between the component weights and body protein weight were fitted to describe the responses. Key results In the allometric equations used to describe the additional weight of each component, at a given body protein weight, resulting from the additional amount of lipid that is deposited in the component as a result of reducing the dietary protein content, only the constant terms were affected. By expressing these constant terms as a proportional increase above the genetically determined level of fatness, described by males on the highest dietary protein feed, equations were derived that described the rate of increase in lipid weight with a change in dietary protein content. Conclusions When predicting the weights of different components in the body by using the allometric relationships between the component weight and body protein weight, equations are now available to correct the weights of the respective components of broilers for the additional amount of lipid that would be deposited as a result of feeding dietary protein contents below that required to achieve the genetically desired level of fatness in each component. Implications With the equations presented herein, one can predict the weights of commercial broiler parts, considering the extra fat deposited due to the dietary balanced protein offered, which may lead to decisions that increase the economic return of poultry production.

Towards Modular and Plug-and-Produce Manufacturing Apps

Industry 4.0 redefines manufacturing systems as smart and connected systems where software solutions provide additional capabilities to the manufacturing equipment. However, the connection of manufacturing equipment with software solutions is challenging due to poor interoperability between different original equipment manufacturers (OEMs), making it difficult to integrate into the manufacturing system. Hence, there is a need for a methodology to develop modular "plug-and-produce" applications in the manufacturing domain to meet the requirements of Industry 4.0. This work investigates the "appification" of manufacturing processes where the goal is to sub-divide the process into independent, re-configurable digital manufacturing applications. In this context, "appification" means separating the digital implementation from the physical implementation of the system by making the former modular and independent so that digital implementations can be re-used without depending on the physical parts of the system. In this paper a framework for the development of such manufacturing "apps" is presented. This framework consists of four main elements: a modular plug-and-produce architecture, a manufacturing apps development kit, a communication protocol, and a construction methodology. The modular plug-and-produce architecture is developed using the recent advances in microservices, containerization, and communication technologies. The manufacturing apps development kit (MAPPDK) has been developed to facilitate the implementation of manufacturing apps using high-level programming languages. MAPPDK allows to control manufacturing equipment from external computational devices. The methodology for developing different modules for different types of manufacturing processes is also provided. The proof of concept is shown experimentally by the "appification" of a sorting process using an industrial robot arm, a gripping end-effector, a third-party vision camera, and an intelligent vision module.