Model Resolution Research Articles

Quantifying the impact of energy system model resolution on siting, cost, reliability, and emissions for electricity generation

Quantifying the impact of energy system model resolution on siting, cost, reliability, and emissions for electricity generation

Resolving sustainable development conflicts caused by vinyl leakage accidents in the USA: From the perspective of graph model under fuzzy preferences with self-confidence

On February 3, 2023, a railroad accident led to the release and combustion of 115,580 gallons of vinyl chloride monomer in East Palestine, Ohio, USA. The large leakage and long-time combustion of vinyl chloride monomer harmed the stability of local sustainable ecosystems and the health of residents, as the burning produced deadly toxins, triggering dissatisfaction from residents and environmental protection organizations. With the COVID-19 pandemic still unfolding globally, decision makers (DMs) in vinyl chloride leakage accidents must consider the existing environmental health uncertainty, potentially leading to uncertainty in their preference cognitive. Thus, this paper proposes a novel fuzzy preference with a self-confidence structure of the graph model for conflict resolution (GMCR) to resolve the sustainable development conflicts caused by the vinyl chloride leakage accident in Ohio. Fully considering the uncertainty of option choice by DMs and the different levels of confidence in DMs’ preference selection, four different fuzzy stability definitions of self-confidence are defined in GMCR. The analysis results suggest the following: (1) During conflicts, the US Norfolk Southern Corp should assume corporate responsibility by setting up a health monitoring system for residents in Ohio; the company should pay for the medical examinations and related care expenses for residents within the scope of the vinyl chloride leakage accident. (2) The negotiation of all stakeholders in conflicts can promote reconciliation. Finally, the analysis process and results of this study can provide guidance to government departments for properly handling major accidents and appeasing affected residents.

Effects of land surface model resolution on fluxes and soil state in the Arctic

Effects of land surface model resolution on fluxes and soil state in the Arctic

MDverse, shedding light on the dark matter of molecular dynamics simulations.

The rise of open science and the absence of a global dedicated data repository for molecular dynamics (MD) simulations has led to the accumulation of MD files in generalist data repositories, constituting the dark matter of MD - data that is technically accessible, but neither indexed, curated, or easily searchable. Leveraging an original search strategy, we found and indexed about 250,000 files and 2000 datasets from Zenodo, Figshare and Open Science Framework. With a focus on files produced by the Gromacs MD software, we illustrate the potential offered by the mining of publicly available MD data. We identified systems with specific molecular composition and were able to characterize essential parameters of MD simulation such as temperature and simulation length, and could identify model resolution, such as all-atom and coarse-grain. Based on this analysis, we inferred metadata to propose a search engine prototype to explore the MD data. To continue in this direction, we call on the community to pursue the effort of sharing MD data, and to report and standardize metadata to reuse this valuable matter.

POSIT: An automated tool for detecting and characterizing diverse morphological features in raster data - Application to pockmarks, mounds, and craters

Accurate detection and characterization of seafloor morphologies are crucial for marine researchers and industries involved in underwater mapping, environmental monitoring, or resource exploration. Although their detection has relied on visual inspection of detailed bathymetries, few efforts to automate the process can be found in the literature. This study presents a novel MatLab computer code called POSIT (Feature Signature Detection) based on the convolution and correlation with a structural element containing the shape to search for. POSIT is successfully tested on both synthetic and real datasets, encompassing marine and terrestrial digital elevation models of different resolution and on a digital image. The centroids of submarine pockmarks and mounds, terrestrial volcanic craters and lunar craters are calculated with zero dispersion and perfect location, and their geometric parameters and confidence are provided.

Dependence of dense filament frontogenesis in a hydrostatic model

In this study, a hydrostatic model - the Navy Coastal Ocean Model (NCOM) is used to analyze the temporal evolution of a cold filament under moderate wind (along / cross filament) and surface cooling forcing conditions. The experimental framework adhered to the setup used in large eddy simulations by Sulllivan and McWilliams (2018). For each forcing scenario, the impact of horizontal resolutions is systematically explored through varies model resolutions of 100 m, 50 m, and 20 m; and the influence of horizontal mixing is investigated by adjusting the Smagorinsky constant within the Smagorinsky horizontal mixing scheme. The role of surface gravity waves is also assessed by conducting experiments both with and without surface wave forcing.The outcomes of our study revealed that while the hydrostatic model is able to predict the correct characteristics/physical appearance of filament frontogenesis, it fails to capture the precise dynamics of the phenomenon. Horizontal mixing parameterization in the model was found to have marginal effect on frontogenesis, and the frontal arrest is controlled by the model's subgrid-scale artificial regularization procedure instead of horizontal shear instability. Consequently, higher resolution is corresponding to stronger frontogenesis in the model. Thus, whether the hydrostatic model can produce realistic magnitude of frontogenesis is purely dependent on the characteristic of the front/filament simulated and model resolution. Moreover, examination of the parameterized effect of surface gravity wave forcing through vertical mixing unveiled a limited impact on frontogenesis, suggesting that the parameterization falls short in representing the real physics of wave-front interaction.

On the Realism of Tropical Cyclone Intensification in Global Storm‐Resolving Climate Models

AbstractThe physical processes governing a tropical cyclone's lifecycle are largely understood, but key processes occur at scales below those resolved by global climate models. Increased resolution may help simulate realistic tropical cyclone intensification. We examined fully coupled, global storm‐resolving models run at resolutions in the range 28–2.8 km in the atmosphere and 28–5 km in the ocean. Simulated tropical cyclone activity, peak intensity, intensification rate, and horizontal wind structure are all more realistic at a resolution of ∼5 km compared with coarser resolutions. Rapid intensification, which is absent at typical climate model resolutions, is also captured, and exhibits sensitivity to how, and if, deep convection is parameterized. Additionally, the observed decrease in inner‐core horizontal size with increasing intensification rate is captured at storm‐resolving resolution. These findings highlight the importance of global storm‐resolving models for quantifying risk and understanding the role of intense tropical cyclones in the climate system.

Spatiotemporally Detailed Quantification of Air Quality Benefits of Emissions-Part II: Sensitivity to Study Parameters and Assumptions.

Adjoint modeling, using U.S. EPA's Community Multiscale Air Quality (CMAQ), has been performed to provide location-specific monetized health benefits from the controls of primary PM2.5 and PM2.5 precursors (NO x , SO2, and NH3) across North America. Source-to-health benefit relationships are quantified using a benefit-per-ton (BPT) metric, accounting for the impacts on premature mortality due to long-term exposure to fine particulate matter. In the base analysis, the approach used a 12 km resolution, four 2-week episodes chosen to capture annual responses, emissions for 2016, and the Global Exposure Mortality Model (GEMM) to link exposures to premature mortality. Here, we investigate the impacts those choices have on results using a range of sensitivity analyses. The choice of four representative episodes led to relatively little bias and error. Finer model resolution, investigated by comparing 36, 12, 4, and 1 km simulations over two urban areas, tended to increase BPT estimates, though the impact was inconsistent between different regions. While BPTs and burden estimates were consistent across resolutions over New York City, they sharply increased for Los Angeles, particularly for NOx and ammonia, leading to 90% increase in burden estimates at 1 km resolution. We find that, for primary PM2.5 emissions, better resolved population distribution is the main contributing factor to higher BPTs, but for secondary precursor emissions (ammonia and NOx), higher model resolution that avoids dilution in coarser grids is more important. Changing emissions from 2016 to 2001 and 2028 resulted in fairly consistent primary PM2.5 BPTs but impacted the BPTs for NOx and ammonia more significantly due to changes in SO2 emissions. We found that BPTs tend to stabilize, as emission changes in 2028 lead to a lower deviation from 2016 BPTs compared to changes from the 2001 episode. The role of the epidemiological model also led to relatively modest uncertainties, 15-30% depending on the species, even when different shapes of concentration-response functions were employed. We found the impact of the choice of CRF to be larger or comparable in size to the reported epidemiological model uncertainties for log-linear CRFs. The adjoining approach proved robust to modeling choices in providing BPT estimates that are highly granular across locations and emitted species.

From SPECT/CT towards absolute quantification? - the case of unilateral condylar hyperplasia of the mandible

BackgroundUnilateral condylar hyperplasia (UCH) of the mandible is a rare condition characterized by asymmetric growth of the mandibular condyles. Bone scintigraphy with SPECT(/CT) is commonly used to diagnose UCH and guide treatment. Still, varying results have been reported using the traditional threshold of 55%:45% in relative tracer uptake. While absolute quantification of uptake on SPECT/CT could improve results, optimal correction and reconstruction settings are currently unknown.MethodsThree anthropomorphic phantoms representing UCH were developed from patient CT volumes and produced using 3D printing technology. Fillable spherical inserts of different sizes (Ø: 8–15 mm) were placed in the condylar positions representing symmetrical and asymmetrical distributions. Recovery coefficients were determined for SPECT/CT using various reconstruction corrections, including attenuation and scatter correction (ACSC), resolution modeling (RM), and partial volume correction (PVC) using phantom measurements. Uptake ratios between condyles and condyle to clivus were evaluated. Finally, the impact of these correction techniques on absolute activity and diagnostic accuracy was assessed in a retrospective patient cohort for the diagnostic threshold of 55%:45%.ResultsThe activity was only partially recovered in all spherical inserts (range: 22.5–64.9%). However, RM improved relative recovery by 20.2–62.3% compared to ACSC. In the symmetric phantoms, the 95% confidence interval (CI) of condyle ratios included the diagnostic threshold (57.6%:42.4%) for UCH when using ACSC potentially leading to false positives, but not for ACSCRM datasets. Partial volume corrections coefficients from the NEMA IQ phantom was positionally dependent, with improvements seen performing PVC using coefficients derived from anthropomorphic phantoms. Retrospective application in a patient cohort showed only a weak linear correlation (R²: 0.25–0.67) and large limits of agreement (9.6–12.5%) between different reconstructions. Up to 44% of patients were reclassified using the 55%:45% threshold. Using clinical outcome data, ACSCRM had highest sensitivity (91%; 95% CI 59–100%) and specificity (66%; 95% CI 47–81%), significantly improving specificity (P = 0.038).ConclusionsAnthropomorphic phantoms were shown to be essential in determining optimal settings for acquisition, reconstruction, and analysis. SPECT/CT reconstructions with attenuation and scatter correction and resolution modeling are recommended and could improve specificity when using the 55%:45% threshold to assess condylar growth.

Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution.

High-spatial resolution MRI produces abundant structural information, enabling highly accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high-spatial resolution MRI data typically can come at the expense of less spatial coverage, lower signal-to-noise ratio (SNR), and longer scan time due to physical, physiological and hardware limitations. In order to overcome these limitations, super-resolution MRI deep-learning-based techniques can be utilised. In this work, different state-of-the-art 3D convolution neural network models for super resolution (RRDB, SPSR, UNet, UNet-MSS and ShuffleUNet) were compared for the super-resolution task with the goal of finding the best model in terms of performance and robustness. The public IXI dataset (only structural images) was used. Data were artificially downsampled to obtain lower-resolution spatial MRIs (downsampling factor varying from 8 to 64). When assessing performance using the SSIM metric in the test set, all models performed well. In particular, regardless of the downsampling factor, the UNet consistently obtained the top results. On the other hand, the SPSR model consistently performed worse. In conclusion, UNet and UNet-MSS achieved overall top performances while RRDB performed relatively poorly compared to the other models.

Multi-Attribute evaluation-based graph model for conflict resolution considering heterogeneous behaviors

The graph model for conflict resolution (GMCR) is a useful tool for modeling and analyzing conflicts. In a conflict, the decision maker (DM)’s evaluation of feasible states is often influenced by multiple attributes. When in different feasible states, DMs may assign different importance to each attribute. Therefore, this paper applies multi-attribute evaluation (MAE) to GMCR and proposes the MAE-based stability definition. In addition, due to differences in relationships and opinions among DMs, opponents will behave differently in response to the action of the focal DM. To analyze the heterogeneous behavior of opponents, this paper proposes a heterogeneous behavior analysis method based on social network analysis (SNA) and opinion similarity. Then, the MAE-based mixed stability definitions are proposed to perform the stability analysis considering heterogeneous behaviors. Finally, this paper applies the proposed method to the Elmira contamination conflict and makes a sensitivity analysis to prove the validity of the proposed method.

Correction to: Projections of North American snow from NA-CORDEX and their uncertainties, with a focus on model resolution

Correction to: Projections of North American snow from NA-CORDEX and their uncertainties, with a focus on model resolution

Communal dialogue and peacebuilding education in volatile terrain: A study of the volatile African region

This article evaluates the adoption of communal dialogue as an education tool for peace building in volatile terrain in Africa, using Benue State, North-Central Nigeria, as a case in point. Benue State has, in the last eight years, been known for constant communal clashes. This article looks at ways to adopt a valid model of conflict resolution to end this struggle. The yearly uproar arising in this region as residents live in constant fear calls for concern. This inquiry collated churns of research using secondary data together with a survey to ensure a tangible solution was proffered. All the local governments in this region were selected, especially where there are consistent struggles, interferences of herdsmen, and insecurities. About 363 copies of the questionnaires were distributed among residents living in this region. The aim is to generate data bordering on peace building education initiatives, as regular conflicts have rampaged this region for over a decade. Expected findings will focus on the best model that can tackle insecurity appropriately. The study's findings show that all the respondents agreed that they see communal dialogue approaches employed as viable tools for peacebuilding education in the region. Important to note is the need to consider the peculiarities of this region. It is crucial to leverage frameworks that best suit this struggle, considering peculiarities in these regions as seen in similar areas in different parts of the world today. We therefore recommend that communal dialogue approaches be properly employed to restore lasting peace.

Impact Assessment of Digital Elevation Model (DEM) Resolution on Drainage System Extraction and the Evaluation of Mass Movement Hazards in the Upper Catchment

Impact Assessment of Digital Elevation Model (DEM) Resolution on Drainage System Extraction and the Evaluation of Mass Movement Hazards in the Upper Catchment

A collaborative planning model of IES containing EHs and multi-energy grids under the premise of demand response as well as wind power uncertainty

The proliferation of renewable energy resources and the incorporation of various types of energy bring opportunities as well as new challenges to the planning and operations within integrated energy systems (IESs). To better characterize multiple uncertain variables within IES, reducing wind power curtailment and minimizing costs, this paper proposes an IES collaborative planning model with EHs, in which uncertain variables are depicted by Z-numbers. Firstly, Z-number incorporates both fuzzy and probabilistic uncertainties, allowing the representation of uncertain variables with credibility information in constraints. Secondly, simplifying Z-numbers into an engineering-applicable method reduces the complexity of model resolution. Thirdly, to fully leverage the complementary transformation characteristics among different energy sources, the optimization model includes decisions on the capacity of energy conversion and energy storage components within EHs. Moreover, outside the EHs, conventional generator dispatches, and the hardening of electric-gas grid decisions are also included. Finally, the model is verified on an IES that involves the coupling of a six-node power system and a six-node gas system, and numerical results validate that wind power output values represented by Z-numbers have a standard deviation of only 0.33 from actual values. Furthermore, different credibility information in Z-numbers significantly impacts planning outcomes; an increased DR credibility can be conducive to reducing wind curtailment with 45KW and help cost-savings with 4.05%.

Validation of Timepix4 energy calibration procedures with synchrotron X-ray beams

The Timepix4 is an application-specific integrated circuit developed by the Medipix4 collaboration. The chip is a 448 × 512 matrix that can be connected, via bump-bonding, to pixelated sensors of various materials and thicknesses, forming application specific detection systems. Among the Timepix4 operating modes, the data-driven Time-of-Arrival - Time-Over-Threshold is a particularly promising mode for spectral imaging applications: data packets are generated every time the charge created by the incoming radiation goes above a pre-defined threshold, allowing the count of the detected particles and their energy measurement. This article investigates the spectroscopic characteristics of a Timepix4 assembly equipped with a 300 μm Si sensor, using monochromatic X-ray beams in the energy range 8.5 keV–40 keV working at the SYRMEP beamline of the Elettra synchrotron. The accuracy and the energy resolution of the reconstructed energy spectra, together with an energy resolution model, will be presented.

The influence of externality in the graph model for conflict resolution under fuzzy preferences

The Graph Model for Conflict Resolution (GMCR) is a flexible and comprehensive methodology for systematically investigating strategic conflicts. However, most existing studies solely focus on internal conflicts among decision makers (DMs), often disregarding the influence of external stakeholders (ESs) on DMs’ preferences. Consequently, this leads to insufficient stability in equilibrium outcomes. The objective of this study is to address the conflict issue faced by DMs with subjective uncertain preferences who are influenced by externality. Building upon the framework of GMCR, this study proposes the graph model for conflict resolution with fuzzy preference based on externality (FEGMCR) which introduces fuzzy numbers to measure both uncertain preferences of DMs and uncertain expectations of ESs. Furthermore, four forms of stability are extended-- Fuzzy Nash Stability based on externality (FER), Fuzzy General Metarationality based on externality (FEGMR), Fuzzy Symmetric Metarationality based on externality (FESMR), and Fuzzy Sequential Stability based on externality (FESEQ). The optimal equilibrium is achieved by dynamically adjusting the weight of the impact of externalities. Finally, the method is applied to the case of plastic ban in Hainan. It is found that the expectations of ESs do change the preferences of DMs and affect the final equilibrium, which provides a sustainable solution for the issue.

FLOOD INUNDATION MAPPING OF GODAVARI RIVER BY USING 2D HEC-RAS MODEL

Due to increasing urbanization, there are various drastic changes taking place in environment these changes are hazardous for human being as well as animal and environment. Effect of environmental degradation can create environmental issues such as flood, drought etc. Out of this flood is the most common and disastrous hazard in the world. Present study utilizes 2D Unsteady flow modelling for flood inundation mapping in the lower Godavari basin for a reach length of 70 km from Sambaigudem in Telanagana district of Ramanujavaram to Damaracherla in Andhra Pradesh district of Nalgonda. For analysis of this 2D flow modelling and inundation mapping 30m resolution DEM is used. From ancient time majority of cities are developed near or on the banks of the river and these cities were affected due to flood during rainy season or due to the high intensity rainfall. As India is among the most vulnerable to flooding because of its geographical features. Therefore, this study is performed to analyze the flood plain and the extent of the affected areas present on or near the bank of Godavari River and provide mitigation measures for it.

Dissipative Particle Dynamics Simulation of Protein Folding in Explicit and Implicit Solvents: Coarse-Grained Model for Atomic Resolution.

Advancements have been made to dissipative particle dynamics (DPD), a robust coarse-grained (CG) simulation method, to study the folded structures of four miniproteins (1L2Y, 1WN8, 1YRF, and 2I9M) in explicit and implicit solvents. In this endeavor, we aim to establish model parametrization and enhance computational efficiency. Unlike traditional CG models that use empirical force parameters, ex-force parameters (r0(ex), , δd, δp) of DPD particles constructed for specific research purposes can be obtained from atomistic molecular dynamics simulations. On the other hand, im-force parameters (r0(im), c, σ) can be derived from ex-DPD simulations, according to the underlying thermodynamic theory. Based on a mapping scheme proposed for the modeling of amino acids, all-atom proteins can be converted into a CG model. Both ex-/im-DPDs are then carried out to investigate the folding pathways of the four mini-proteins. Structural analysis of the RMSDs shows that the im-simulated proteins have greater structural similarity to native proteins than the ex-simulated ones. The constructed CG models achieve a resolution of Angstrom (Å), a level normally associated with atomic models. Additionally, speed tests reveal that im-DPD accelerates the simulation process and significantly improves simulation efficiency.

Conflict resolution in the customary village governance administration of Baduy, Tengger, and Samin ethnic groups in Indonesia

In Indonesia, the village government organization is part of local democracy. This includes the local democracy in indigenous villages. Indigenous villages have their own customary rules for implementing village elections. They have their own conflict resolution systems in implementing the village government. The implementation of the indigenous village governance leaves conflicts. So, there is a need for a suitable model for resolving problems in the implementation of village elections. The method used in this research is the qualitative research method with the juridical empirical approach. The locus of this research is in the Baduy, Tengger, and Samin indigenous village communities. The conflict resolution model in the administration of the Baduy, Tengger, and Samin customary villages differs in the right mechanism, but in substance, the resolution model is the same, as they use a deliberation model for consensus. In resolving conflicts, indigenous peoples fully submit to traditional leaders. The provincial and the regency/city governments are expected to give greater attention to the conditions of villages with customary government characteristics.