Generic Scenario Research Articles

Optimizing the Focusing Performance of Non-Ideal Cell-Free mMIMO Using Genetic Algorithm for Indoor Scenario

This paper proposes a genetic algorithm (GA) combined with ray tracer to generate a cell-free topology of massive MIMO (mMIMO) for the optimal focusing performance serving multiple users. The realistic hardware impairment, for instance the non-ideal power amplifier, is taken into account of the system modeling and topology optimization. To the best of our knowledge, this is the first attempt to apply GA in optimizing the hardware-impaired multi-user cell-free mMIMO. Although the demonstrated numerical analysis is for indoor scenario, the proposed approach is transferable for generic scenarios. In GA, the base station (BS) antennas’ placement is encoded with an adjusted binary matrix representation, which is straightforward for the subsequent genetic operations. The explored candidates by GA can evolve beyond the parents, where the fitness of individuals is evaluated dynamically via a ray tracer radio channel simulator. Compared to the traditional GA, our proposed GA can find better solutions with a faster convergence speed. The algorithm provides near-optimal results in experiments, applicable to generic environment with multiple mobile users and different signal-to-interference-plus-noise ratios.

Revealing Double White Dwarf Mergers with Multi-messenger Signals

A significant number of double white dwarfs (DWDs) are believed to merge within the Hubble time due to the gravitational wave (GW) emission during their inspiraling phase. The outcome of a DWD system is either a type Ia Supernova as the double-degenerate model, or a massive, long-lasting merger remnant. Expected multi-messenger signals of these events will help us to distinguish detailed merging physical processes. In this work, we aim to provide a generic scenario of DWD merging, investigate the emission of all major messengers, with a focus on GWs and neutrinos. Our goal is to provide some guidance for current and future (collaborative) efforts of multi-messenger observations. Throughout the merging evolution of a DWD system, different messengers (GW, neutrino and electromagnetic wave) will dominate at different times. In this work, we show that DWD merger events located at the distance of 1 kpc can indeed produce detectable signals of GWs and neutrinos. The GW frequency is in 0.3–0.6 Hz band around 10 days before tidal disruption begins. We estimate that in optimistic situations, the neutrino number detected by upcoming detectors such as JUNO and Hyper-Kamiokande can reach O(1) for a DWD merging event at ∼1 kpc.

Environmental Noise Assessment of Holding Approach Procedures Using a Multi-Level Simulation Framework

Computational models of sufficient quality are indispensable to quantitatively assess aircraft noise reduction measures. Within this study, a multi-level simulation framework is established in order to predict the environmental noise of holding approach procedures by coupling simulation models from three different domains: flight performance calculation employing the base of aircraft data (BADA), jet engine performance using the software Gasturb and aircraft noise simulations based on the software sonAIR. Two different concepts of holding approach procedures are investigated, namely, the vertical holding stack and the linear hold point merge. The study is conducted considering generic air traffic scenarios at a single-runway airport. Thereby, the investigated air traffic is based on a statistical analysis of traffic data at existing airports and thus assumed to be representative. As the aircraft’s noise emission depends on both the aircraft and the engine performance, reliable results can be expected only if all individual challenges and interdependencies are accounted for simultaneously. Addressing this challenge is the main contribution of the presented work. The presented results show the plausibility of the proposed multi-level simulation framework, thus supporting its use to investigate the environmental noise impact of air traffic scenarios.

Need to go further: using INLA to discover limits and chances of burglaries’ spatiotemporal prediction in heterogeneous environments

Near-repeat victimization patterns have made predictive models for burglaries possible. While the models have been implemented in different countries, the results obtained have not always been in line with initial expectations; to the point where their real effectiveness has been called into question. The ability to predict crime to improve preventive policing strategies is still under study. This study aims to discover the limitations to and the success of the models that attempt to predict burglaries based on spatiotemporal patterns of the risk of break-ins spreading in geographic proximity to the initial break-ins. A spatiotemporal log-Gaussian Cox process is contemplated to model the generic near-repeat victimization scenario and adjusted using the Integrated Nested Laplace Approximation (INLA) methodology. This approach is highly suitable for studying and describing the near-repeat phenomenon. However, predictions obtained with INLA are quite monotonous, of low variability and do not reproduce well the local and short-term dynamics of burglaries for predictive purposes. The conclusion is that predictive models cannot be restricted exclusively to distance decay risk, but they must be designed to detect other types of spatiotemporal patterns which, among other possibilities, open up the possibility of correlating distant events and clusters. Although other studies have already highlighted this problem, the proposal here is to go one step further and clearly extend the near-repeat spatial patterns to achieve better prediction results.

Covariant entanglement wedge cross-section, balanced partial entanglement and gravitational anomalies

The balanced partial entanglement (BPE) was observed to give the reflected entropy and the entanglement wedge cross-section (EWCS) for various mixed states in different theories [1,2]. It can be calculated in different purifications, and is conjectured to be independent from purifications. In this paper we calculate the BPE and the EWCS in generic covariant scenarios in two-dimensional CFTs with and without gravitational anomalies, and find that they coincide with the reflected entropy. In covariant configurations we determine the partition for the purifying system with the help of the gravitational anomalies, and we extend our discussion to topological massive gravity (TMG). We give the first prescription to evaluate the entropy quantity associated to the EWCS beyond Einstein gravity, i.e. the correction to the EWCS from the Chern-Simons term in TMG. Apart from the gravity theory and geometry, further input from the mixed state should be taken into account.

Multiband Effects in the Superconducting Phase Diagram of Oxide Interfaces

AbstractA dome‐shaped phase diagram of superconducting critical temperature upon doping is often considered as a hallmark of unconventional superconductors. This behavior, observed in SrTiO3‐based interfaces, whose electronic density is controlled by field‐effect, has not been explained unambiguously yet. Here, a generic scenario for the superconducting phase diagram of these oxide interfaces is elaborated based on transport experiments on a double‐gate LaAlO3/SrTiO3 field‐effect device and Schrödinger–Poisson numerical simulations of the quantum well. The optimal doping point of maximum Tc is ascribed to the transition between a single‐gap and a fragile two‐gap s±‐wave superconducting state involving bands of different orbital character. Close to this point, a bifurcation in the dependence of Tc on the carrier density, which can be controlled by the details of the doping execution, is observed experimentally and reproduced by numerical simulations. Where doping with a back‐gate triggers the filling of a new subband and initiates the overdoped regime, doping with a top‐gate delays the filling of the subband and maintains the 2D electron gaz in the single‐gap state of higher Tc. Such a bifurcation, whose branches can be followed reversibly, provides a generic explanation for the dome‐shaped superconducting phase diagram that could be extended to other multiband superconducting materials.

A generic scenario analysis of end-of-life plastic management: Chemical additives

Plastic growing demand and the increment in global plastics production have raised the number of spent plastics, out of which over 90% are either landfilled or incinerated. Both methods for handling spent plastics are susceptible to releasing toxic substances, damaging air, water, soil, organisms, and public health. Improvements to the existing infrastructure for plastics management are needed to limit chemical additive release and exposure resulting from the end-of-life (EoL) stage. This article analyzes the current plastic waste management infrastructure and identifies chemical additive releases through a material flow analysis. Additionally, we performed a facility-level generic scenario analysis of the current U.S. EoL stage of plastic additives to track and estimate their potential migration, releases, and occupational exposure. Potential scenarios were analyzed through sensitivity analysis to examine the merit of increasing recycling rates, using chemical recycling, and implementing additive extraction post-recycling. Our analyses identified that the current state of plastic EoL management possesses high mass flow intensity toward incineration and landfilling. Although maximizing the plastic recycling rate is a reasonably straightforward goal for enhancing material circularity, the conventional mechanical recycling method requires improvement because major chemical additive release and contamination routes act as obstacles to achieving high-quality plastics for future reuse and should be mitigated through chemical recycling and additive extraction. The potential hazards and risks identified in this research create an opportunity to design a safer closed-loop plastic recycling infrastructure to handle additives strategically and support sustainable materials management efforts to transform the US plastic economy from linear to circular.

How Transport Modelling affects the building Life Cycle Assessment (LCA) results: A Case Study Analysis

The Life Cycle Assessment (LCA) of a building involves the use of various types of information about the building, including the products, processes, and services related to the building throughout its life cycle. The modelling of the transport process can be complex and may be performed based on a variety of approaches and assumptions. With existing approaches, the most accurate results those closest to the real scenario, are calculated once the building has already been built. Other approaches are based on estimations at the design stage using generic scenarios and data sources. The variation of the LCA results when employing different modelling options for transport modules is studied herein. To this end, and to identify the possible errors or dispersion of the LCA results related to the various transport modelling options, transport impacts are calculated using a case study, whereby five different modelling options are compared. The results show that the transport impact difference between the lowest values (the real scenario) and the highest values (normalised detailed scenario) is approximately 30%. To conclude, efforts should be made to better define the default scenarios, especially regarding transport distances and the correction for volumetric capacity of the transport vessels, adapted to the real scenario.

Secure Transmit Beamforming for Radar-Communication System Without Eavesdropper CSI

This article studies the transmit beamforming security in the dual-functional radar-communication (DFRC) system, where the radar beam also serves as the artificial jamming to suppress potential eavesdropper channels. Unlike previous researches, which assumed that the lone target might be a potential eavesdropper on the adversary side, this paper analyses a more generic scenario in which the eavesdroppers’ channel state information (CSI) is unknown. The eavesdropping rate should be limited to guarantee transmission confidentiality, which is intractable owing to the unknown CSI. To address this issue, we present the long-term eavesdropping signal-to-interference-plus-noise ratio (SINR) as a more tractable security metric. Based on the long-term eavesdropping SINR, the sum rate maximization (SRM) and jamming power maximization (JPM) transmission scheme are investigated. For the SRM scheme, we propose a zero-forcing (ZF) suboptimal algorithm to solve the non-convex fractional programming (FP) problem, and for the JPM scheme, the resultant problem is solved via the semidefinite relaxation (SDR) technique. Finally, numerical results validate the effectiveness of the proposed beamforming approaches.

Digital Twins: From Conceptual Views to Industrial Applications in the Electrical Domain

This article reviews various conceptual views behind the digital twins paradigm, highlights software technologies to develop digital twins, analyzes the use of digital twins during the lifecycle of industrial assets, and discusses a generic scenario from the electricity domain.

Observational Constraints on Cosmic-Ray Escape from Ultrahigh-energy Accelerators

Interactions of ultra-high energy cosmic rays (UHECRs) accelerated in specific astrophysical environments have been shown to shape the energy production rate of nuclei differently from that of the secondary neutrons escaping from the confinement zone. Here, we aim at testing a generic scenario of in-source interactions through phenomenological modeling of the flux and composition of UHECRs. We fit a model in which nucleons and nuclei follow different particle energy distributions to the all-particle energy spectrum and proton spectrum below the ankle energy and distributions of maximum shower depths above this energy, as inferred at the Pierre Auger Observatory. We obtain that the data can be reproduced using a spatial distribution of sources that follows the density of extragalactic matter on both local and large scales, providing hence a realistic set of constraints for the emission mechanisms in cosmic accelerators, for their energetics, and for the abundances of elements at escape from their environments. While the quasi monoelemental increase of the cosmic-ray mass number observed on Earth from ≃2 EeV up to the highest energies calls for nuclei accelerated with a hard spectral index, the inferred flux of protons down to ≃0.6 EeV is shown to require for this population a spectral index significantly softer than that generally obtained up to now. We demonstrate that modeling UHECR data across the ankle substantiates the conjecture of in-source interactions in a robust statistical framework, although pushing the mechanism to the extreme.

Distribution chain diagrams for fresh fruit supply chains: A baseline for emission assessment

Background: Globalisation has undoubtedly revolutionised the way modern society functions by connecting different people, economies, cultures and technology. This integration depends on the adequate movement of goods by increasingly more complex and longer global supply chains (SCs). The structure of the distribution chain and the individual activities that jointly facilitate the transportation of commodities such as fresh fruit have not been well defined, making it difficult and ambiguous to determine greenhouse gas emissions. Mapping the various distribution scenarios of fruit and stating the emission-generating activities not only enable the analysis and management of these activities but also provide a basis for calculating emissions.Objectives: The key objective is to describe all the physical emission-generating distribution activities that take place during the international export of fresh fruit from South Africa. These activities were used to create distribution chain diagrams that define the structure of fresh fruit distribution.Method: To identify activities, a literature review, direct observation of distribution activities at logistical facilities and unstructured interviews with operational managers at these facilities were performed. Scenario planning was used to combine generic activities into realistic distribution chain diagrams. The activities and diagrams were validated by semistructured interviews with four industry experts.Results: Following the identification of emission-generating activities, five generic distribution chain diagrams were created that should represent all possible distribution scenarios for fresh fruit.Conclusion: The generic distribution scenarios not only capture the various methods by which fresh fruit is exported from South Africa but also form the basis of seven important emission-related managerial practices.

Rescuing high-scale leptogenesis using primordial black holes

We explore the interplay between light primordial black holes (PBH) and high-scale baryogenesis, with a particular emphasis on leptogenesis. We first review a generic baryogenesis scenario where a heavy particle, $X$, with mass, ${M}_{X}$, produced solely from PBH evaporation decays to generate a baryon asymmetry. We show that the viable parameter space is bounded from above by ${M}_{X}\ensuremath{\lesssim}{10}^{17}\text{ }\text{ }\mathrm{GeV}$ and increases with decreasing ${M}_{X}$. We demonstrate that regions of the leptogenesis parameter space, where the lightest right-handed neutrino (RHN) mass ${M}_{{N}_{1}}\ensuremath{\gtrsim}{10}^{15}\text{ }\text{ }\mathrm{GeV}$ and neutrino mass scale ${m}_{\ensuremath{\nu}}\ensuremath{\gtrsim}0.1\text{ }\text{ }\mathrm{eV}$, excluded in standard cosmology due to $\mathrm{\ensuremath{\Delta}}L=2$ washout processes, become viable with the assistance of light PBHs. This scenario of PBH-assisted leptogenesis occurs because the PBHs radiate RHNs via Hawking evaporation late in the Universe's evolution when the temperature of the thermal plasma is low relative to the RHN mass. Subsequently, these RHNs can decay and produce a lepton asymmetry while the washout processes are suppressed.

Experimental and Computational Verification of a New Remote Monitoring System Design for Spent Fuel Dry Cask Safeguards Using Small-Scale, Generic Diversion Scenarios

Dry casks will be a prevalent spent nuclear fuel (SNF) storage option until solutions for long-term storage or disposal are deployed. A dry cask storing 32 pressurized water reactor fuel assemblies will likely contain about 20 significant quantities of plutonium, so these structures require effective safeguards monitoring. An external remote monitoring system (RMS) is proposed to advance the current dry cask safeguards regime which relies on containment and surveillance. The objectives of this study were to assess the performance of the external RMS as a detection system and to develop a simulation approach for estimating measurements. Small-scale experiments of generic neutron source diversions mimicking SNF diversion from a dry cask were conducted and the nondetection probability was calculated for a variety of measurement times. MCNP simulations were carried out to assess the degree to which the measurement results could be predicted. A previous simulation methodology was advanced to consider uncertainty in the activity of sources being measured. The study concluded that the external RMS performs well as a neutron detection system and that MCNP simulation is a viable tool both for predicting measurements made with the external RMS and for calculating nondetection probabilities of hypothetical, generic diversion scenarios.

Scenario analysis of fish escapes in Norwegian aquaculture for implementation of barrier management and improved learning from accidents

Learning from accidents is decisive for establishing barriers to prevent future accidents and ensuring safety in socio-technical systems. Farmed fish escape is a major concern in the aquaculture industry and there is limited understanding of the accident scenarios involving fish escape. Hence, the systematic analysis of information and data about these types of near accidents and accidents may reveal contributing causes. The objective of this article is to present data and scenarios based on the investigation of 745 fish escape accidents and near accidents reported to the Norwegian Directorate of Fisheries from January 2006 to August 2019. The aim is to derive the direct and underlying causes and develop generic scenarios for fish escape, which can be used for improved reporting of near accidents and accidents. The paper discusses the limitations of current reporting systems, suggests a new categorization scheme for the Directorate of Fisheries to enhance the industry and authorities’ learning from fish escape events, and incorporates new types of fish farms emerging in the industry. Further, the study results can support barrier management and emergency planning, since they help understand the causes of fish escapes. This may be used for analyzing whether existing accident prevention strategies and barriers are sufficient or if additional barriers need to be implemented by fish farm operators.

Development of a gamma ray dose rate calculation and mapping tool for Lagrangian marine nuclear emergency response models

This paper presents the development and testing of a gamma radiation dose rate calculation model for the marine environment, and evaluates the potential use for such a model in both short term nuclear emergency response management and emergency response planning. This is believed to be the first implementation of a full field gamma radiation mapping model (including air attenuation and buildup) to be incorporated within a Lagrangian marine dispersion model. Calculated surface gamma ray dose rates for nine generic release scenarios are presented and used to undertake an emergency countermeasure optioneering assessment.

Physics-Driven Deep Learning Inversion with Application to Magnetotelluric

Due to the strong capability of building complex nonlinear mapping without involving linearization theory and high prediction efficiency; the deep learning (DL) technique applied to solve geophysical inverse problems has been a subject of growing interest. Currently, most DL-based inversion approaches are fully data-driven (namely standard deep learning), the performance of which largely depends on the training sample sets. However, due to the heavy burden of time and computational resources, it can be challenging to supply such a massive and exhaustive training dataset for generic realistic exploration scenarios and to perform network training. In this work, based on the recent advances in physics-based networks, the physical laws of magnetotelluric (MT) wave propagation is incorporated into a purely data-driven DL approach (PlainDNN) and thus builds a physics-driven DL MT inversion scheme (PhyDNN). In this scheme, the forward operator modeling MT wave propagation is integrated into the network training loop, in the form of minimizing a hybrid loss objective function composed of the data-driven model misfit and physics-based data misfit, to guide the network training. Consequently, the proposed PhyDNN method will take the advantage of the fully data-driven DL and conventional physics-based deterministic methods, allowing it to deal with complex realistic exploration scenarios. Quantitative and qualitative analysis results demonstrate that the PhyDNN can honor the physical laws of the MT inverse problem, and with other conditions unchanged, the PhyDNN outperforms the PlainDNN and the classical deterministic Occam inversion method. When processing field data, the PhyDNN method yields considerably impressive inversion results compared to the Occam method, and the corresponding simulated MT responses agree well with the real measurements, which confirms the effectiveness and applicability of the PhyDNN method.

Mechanical model for the motion of RPV internals affecting neutron flux noise

In the decade after 2000, the amplitude of the neutron flux fluctuations in German 1300 MWe class PWR built by Kraftwerk Union (KWU) increased and later decreased significantly. To further investigate the hypothesis that changes in the mechanical properties of the fuel assemblies (FAs) and subsequent stronger mechanical oscillations of fuel assemblies and other RPV internals are responsible for the observations and to find possible excitation mechanisms, a simple mechanical model is developed. It describes the dynamic motion response of the mechanically coupled system of Reactor Pressure Vessel (RPV), core barrel and a row of fuel assemblies and takes reactive fluidic forces into account. To determine the components to be considered in this model, RPV internals with an effect on neutron flux are identified in a prior step.The dynamic answers of the model to generic excitation scenarios and parametric studies reveal distinct properties of the system. They indicate 1) that fluidic near-field coupling can equalize the fuel assemblies’ reaction amplitudes within a certain region regardless of their individual stiffnesses, 2) that the fluid must be part of the oscillation, 3) that a non-periodicity might stem from a superposition and interaction of several oscillators, 4) that a local excitation source does not spread or synchronize over the whole core, 5) that a neglection or separate consideration of the RPV and core barrel may be justified in some cases. The findings altogether affirm that core-wide oscillations of the fluid flow leading to a simultaneous oscillation of individual fuel assembly groups, possibly including bidirectional effects between fluid and structure, in combination with the changes of the fuel assemblies’ mechanical properties, might be responsible for the temporary increase of neutron flux fluctuations observed in PWR built by KWU.A variant of the mechanical model was studied in a full core investigation with coupled neutron kinetics simulations. These simulations qualitatively reproduce important features of measurement data, while being overall too small in amplitude to explain the observations quantitatively, which confirmed the necessity of considering further effects.

Dynamics of expectations in the bioeconomy—Hopes, disillusionments, and conflicting futures

Abstract The initial European Union bioeconomy policies have been criticized for their overriding economic emphasis at the cost of social and environmental sustainability. The updated policy aims to respond to more ambitious sustainability goals but fails to do so coherently. In this article, we examine the dynamics of bioeconomy expectations. We analyze the development of bioeconomy policy as a technoscientific imaginary by dissecting the changed expectations, their underlying tensions, and the directions to which their combinations guide policymaking. We find that the revised expectations are contradictory and culminate in two key tensions regarding the bioeconomy’s expected scale and socioeconomic paradigm. To enable assessment of the outcomes of conflicting expectations, we examine images of potential futures that rise up from combinations of the key tensions. For this, we use a framework of the four generic scenario narratives. The analysis provides a tool for reflection for assessing the directions and priorities of evolving bioeconomy discourse and policy.

Improving defensive air battle management by solving a stochastic dynamic assignment problem via approximate dynamic programming

Military air battle managers face several challenges when directing operations during quickly evolving combat scenarios. These scenarios require rapid assignment decisions to engage moving targets having dynamic flight paths. In defensive operations, the success of a sequence of air battle management decisions is reflected by the friendly force’s ability to maintain air superiority and defend friendly assets. We develop a Markov decision process (MDP) model of a stochastic dynamic assignment problem, named the Air Battle Management Problem (ABMP), wherein a set of unmanned combat aerial vehicles (UCAV) must defend an asset from cruise missiles arriving stochastically over time. Attaining an exact solution using traditional dynamic programming techniques is computationally intractable. Hence, we utilize an approximate dynamic programming (ADP) technique known as approximate policy iteration with least squares temporal differences (API-LSTD) learning to find high-quality solutions to the ABMP. We create a simulation environment in conjunction with a generic yet representative combat scenario to illustrate how the ADP solution compares in quality to a reasonable, closest-intercept benchmark policy. Our API-LSTD policy improves mean success rate by 2.8% compared to the benchmark policy and offers an 81.7% increase in the frequency with which the policy performs perfectly. Moreover, we find the increased success rate of the ADP policy is, on average, equivalent to the success rate attained by the benchmark policy when using a 20% faster UCAV. These results inform military force management and defense acquisition decisions and aid in the development of more effective tactics, techniques, and procedures.