Extreme Parameters Research Articles

Trustworthiness analysis of heuristic routing algorithm with special constraints for autonomous vehicles in surveillance and coverage operations

This article aims to develop a fast, trustworthy routing algorithm for autonomous vehicles without requiring learning data, where the routing problem with special constraints and features is an extended version of the orienteering problem. For this, firstly, the method for selecting trustworthiness requirements is discussed to map relevant trustworthiness methods to stages in the system lifecycle. Then, a heuristic approach is proposed to automate mission planning within a limited time. Routing is handled through a greedy algorithm that selects tasks based on their distance to a baseline path and score. B-spline path smoothing is implemented for smooth and continuous routes. The results are examined in terms of robustness, explainability, transparency, reproducibility, and non-technical requirements. Scenarios with extreme parameters are generated for validation and testing. The algorithm demonstrates promising performance and fulfils the selected trustworthiness requirements, indicating that classical techniques remain significant candidates for fast, reliable, and unsupervised routing solutions.

Geomagnetic dipole stability and zonal flows controlled by mantle heat flux heterogeneities

Abstract Palaeomagnetic evidence shows that the behaviour of the geodynamo has changed during geological times. These changes are visible through variations in the strength and stability of the magnetic dipole. Variations in the heat flux at the core-mantle boundary (CMB) due to mantle convection have been suggested as one possible mechanism capable of driving such a change of behaviour. This work aims at acquiring a more complete understanding of how lateral heterogeneities of the CMB heat flux affect the geodynamo while other relevant parameters are pushed towards realistic values. For this purpose, we ran geodynamo simulations with degree 1 and 2 spherical harmonic patterns of heat flux at the CMB. Several geodynamo models are used, ranging from standard numerical dynamos to more extreme parameters, including strong field cases and turbulent cases. We show that heat flux heterogeneities with amplitudes compatible with our knowledge of mantle convection history can favour multipolar dynamos. The multipolar transition is associated with a disruption of westward flows either through eastward thermal winds or through a loss of equatorial symmetry. Strong field dynamo models are found to have larger westward flows and are less sensitive to heat flux heterogeneities. Furthermore, we find that the dipolar fraction of the magnetic field correlates with $M_{Za}^*=\dfrac{\Lambda _{Za}}{Rm_{Za}^2}$ where ΛZa is the zonal antisymmetric Elsasser number and RmZa is the zonal antisymmetric magnetic Reynolds number. Importantly, $M_{Za}^*$ estimated for the Earth’s core is consistent with a reversing dipolar magnetic field. Within the range of $M_{Za}^*$ susceptible to reversals, breaking the equatorial symmetry or forcing eastward zonal flows through an equatorial cooling of the core consistently triggers reversals or a transition towards multipolar dynamos in our simulations. Our results support that time variations of heat-flux heterogeneities driven by mantle convection through Earth’s history are capable of inducing the significant variations in the reversal frequency observed in the palaeomagnetic record.

Ramsey simplicity of random graphs

Abstract A graph $G$ is $q$ -Ramsey for another graph $H$ if in any $q$ -edge-colouring of $G$ there is a monochromatic copy of $H$ , and the classic Ramsey problem asks for the minimum number of vertices in such a graph. This was broadened in the seminal work of Burr, Erdős, and Lovász to the investigation of other extremal parameters of Ramsey graphs, including the minimum degree. It is not hard to see that if $G$ is minimally $q$ -Ramsey for $H$ we must have $\delta (G) \ge q(\delta (H) - 1) + 1$ , and we say that a graph $H$ is $q$ -Ramsey simple if this bound can be attained. Grinshpun showed that this is typical of rather sparse graphs, proving that the random graph $G(n,p)$ is almost surely $2$ -Ramsey simple when $\frac{\log n}{n} \ll p \ll n^{-2/3}$ . In this paper, we explore this question further, asking for which pairs $p = p(n)$ and $q = q(n,p)$ we can expect $G(n,p)$ to be $q$ -Ramsey simple. We first extend Grinshpun’s result by showing that $G(n,p)$ is not just $2$ -Ramsey simple, but is in fact $q$ -Ramsey simple for any $q = q(n)$ , provided $p \ll n^{-1}$ or $\frac{\log n}{n} \ll p \ll n^{-2/3}$ . Next, when $p \gg \left ( \frac{\log n}{n} \right )^{1/2}$ , we find that $G(n,p)$ is not $q$ -Ramsey simple for any $q \ge 2$ . Finally, we uncover some interesting behaviour for intermediate edge probabilities. When $n^{-2/3} \ll p \ll n^{-1/2}$ , we find that there is some finite threshold $\tilde{q} = \tilde{q}(H)$ , depending on the structure of the instance $H \sim G(n,p)$ of the random graph, such that $H$ is $q$ -Ramsey simple if and only if $q \le \tilde{q}$ . Aside from a couple of logarithmic factors, this resolves the qualitative nature of the Ramsey simplicity of the random graph over the full spectrum of edge probabilities.

Unified genus-1 potential and a parametric perturbative/nonperturbative relation

We study a parametric deformation of the unified genus-1 anharmonic potential and derive a parametric form of perturbative/nonperturbative (P/NP) relation, applicable across all parameter values. We explicitly demonstrate that the perturbative expansion around the perturbative saddle is sufficient to generate all the nonperturbative information in these systems. Our results confirm the known results in the literature, where the cubic and quartic anharmonic potentials are reproduced under extreme parameter values, and go beyond these known results by developing the nonperturbative function of real and complex instantons solely from perturbative data. Published by the American Physical Society 2024

Uncertain future and uncertain projections: assessing extinction risks in European salamanders from projected chytrid fungus invasion using IUCN Criterion E

Amphibians are among the most threatened vertebrates globally, and their conservation status continues to decline. In the updated Global Amphibian Assessment (GAA2), the use of IUCN Criterion E, which projects extinction risks through quantitative models, highlighted southern Europe as a hotspot for salamander extinction risk due to the risk of invasion by the fungal pathogen Batrachochytrium salamandrivorans (Bsal). In particular, for five Italian salamander species, risk categories were elevated significantly based on Criterion E, from Vulnerable or lower to Endangered or Critically Endangered. This increased reliance on Criterion E raises concerns regarding its treatment of uncertainty, as these projections depend heavily on assumptions about Bsal spread, environmental suitability, and host dynamics. Limited exploration of alternative scenarios and reliance on extreme parameter values ​​may result in inflated extinction risk estimates. We emphasize the need for improved documentation of uncertainty and integration of diverse expert opinions in extinction risk assessments, to balance proactive conservation planning with robust scientific methodology.

Evaluation of extreme depyrogenation conditions on the surface hydrolytic resistance of glass containers for pharmaceutical use.

This paper is the result of a round robin activity run by the Technical Committee TC12, Pharma Packaging, of the International Commission on Glass (ICG). The study was motivated by a concern about the risk that the depyrogenation treatment of glass vials, when performed in an abnormal way that deviates from the usual procedure, may have a negative impact on the hydrolytic resistance of the container inner surface. The study was executed by using 10 ml clear type I Borosilicate glass vials representing four different compositions. For the applied depyrogenation process extreme parameters were chosen to with maximum temperature up to 400°C, exposure times up to 72 hours and different amounts of residual water inside as starting conditions. Those treated samples were tested in seven different laboratories as a round robin test.. A large amount of data was obtained, which clearly indicate that the hydrolytic resistance performance of the Type I Borosilicate glass vials is not affected even by such extreme depyrogenation conditions (e.g. 400°C, 72hours and not perfect dried inside). This is an important and useful result, both for glass and pharma companies, based on the 12.000 analytical data collected during the interlaboratory activity.

Applying clustered artificial neural networks to enhance contaminant diffusion prediction in geotechnical engineering

This paper introduces a novel approach using Clustered Artificial Neural Networks (CLANN) to address the challenge of developing predictive models for multimodal dataset with extreme parameter values. The CLANN method strategically decomposes the dataset, derived from Finite Element Analysis (FEA), into clusters, each representing distinct diffusion behaviors, and applies specialized neural networks within these clusters. The CLANN model was rigorously evaluated and demonstrated superior accuracy and consistency compared to traditional methods such as the Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy expert systems. While these conventional models struggled to capture the full range of diffusion dynamics, particularly under extreme conditions, CLANN consistently provided predictions that closely aligned with the actual FEA data across all scenarios. The versatility of the CLANN approach extends beyond its application to soil contamination. Its ability to handle complex, multimodal datasets suggests that this methodology can be generalized to a wide range of scientific and engineering problems characterized by similar data structures. This makes CLANN not only a powerful tool for geotechnical engineers but also a promising framework for broader applications where traditional models fall short. The findings of this study pave the way for more accurate, reliable, and adaptable predictive modeling in diverse domains, enhancing our ability to manage and mitigate environmental and engineering challenges.

Fluvial Sediment Load Characteristics from the Yangtze River to the Sea During Severe Droughts

Most river deltas worldwide are located in well-developed, densely populated lowland regions that face challenges from accelerated sea level rise. Deltas with morphological equilibrium are the foundation for associated prosperous economies and societies, as well as for preserving ecological fragile environments. And for deltas to be in morphological equilibrium, sufficient fluvial sediment supplies are fundamental. Severe droughts have significant impacts on the sediment load discharged to the sea, but this is considerably less studied compared to flooding events. This study examines the characteristics of Yangtze River sediment flowing toward the East China Sea during severe droughts. The effect of the Three Gorges Dam (TGD) was investigated by comparing the difference before and after its construction in 2003. Results indicate that the sediment load from the Yangtze River to the sea has experienced a more pronounced decrease during severe drought years since 2003. The primary cause is a substantial reduction in sediment supply from the upper reaches, resulting from the impoundment of the Three Gorges Reservoir created in 2003 and the construction of additional major reservoirs in the upper reach thereafter. Simultaneously, this is accompanied by the fining of sediment grain size. The fining of sediment and considerably reduced sediment load discharged to the sea during severe droughts after 2003 are likely to accelerate the erosion of the Yangtze subaqueous delta. The rating parameter values during severe drought years fall within the range observed in normal years, indicating that these drought events do not align with extreme rating parameter values. Less than 30% of the average discrepancy between measured and reconstructed sediment loads in severe drought years before 2003, and approximately 10% of the discrepancy after 2003, demonstrate the feasibility of reconstructing sediment loads for severe drought events using a sediment rating curve. This rating curve is based on daily water discharge and sediment concentration data collected during the corresponding period. These findings indicate that the rating curve-based reconstruction of sediment load performs well during severe droughts, with relative error slightly exceeding the average error of normal years prior to 2003 and approaching that observed after 2003. This study provides insights on sediment management of the Yangtze River system, including its coastal zone, and is valuable for many other large river systems worldwide.

Improving ecological modeling: Integrating CNOP-P and adjoint assimilation in a coupled ecological model

Ecological modeling is an important methodology for studying the spatio-temporal evolution of marine ecosystem. Given the significant role of model parameters as a major source of uncertainty in ecological models, we propose a novel approach by combining the Conditional Nonlinear Optimal Perturbation related to Parameters (CNOP-P) method with the adjoint assimilation method to enhance predictive accuracy. CNOP-P denotes the parameter perturbation that leads to the greatest deviation of the model's development from the reference state. In comparison to other sensitivity analysis methods, this combined approach proves to be more efficient. Considering the nonlinearity of the model structure, the maximum development of the model does not consistently align with the extreme parameter values within the confidence interval. Minor parameter errors can lead to substantial model development, significantly impacting the precision of ecological models. Notably, traditional sensitivity analysis methods such as one-at-a-time (OAT) sensitivity analysis and global sensitivity analysis (GSA) methods fail to capture this characteristic. On the other hand, the GSA methods incur substantial computational costs and tends to overestimate the sensitivity of the most sensitive parameters while underestimating the sensitivity of less sensitive parameters. The combined approach of CNOP-P and adjoint assimilation enables the assimilation of satellite data and the simultaneous optimization of model parameters alongside the CNOP-P calculations. This integration substantially improves both efficiency and precision of the ecological model, thereby improving predictive skill.

Development of Rainfall Intensity Duration Frequency Curves for Debre Tabor Town, Ethiopia Using Non-stationary Method

Stationary rainfall intensity duration frequency curves have historically influenced urban infrastructure designs. In contrast to the stationary model, which takes constant parameters into account throughout the observation periods, the non-stationary method takes into account changes in the extreme parameters that determine the distribution of precipitation over time. The parameters were estimated using maximum likelihood estimator method. The best model were computed using the R-studio software by comparing information criteria then model parameters, return levels, rainfall intensity are computed. The National Meteorological Agency, situated in Addis Ababa, Ethiopia, provided the essential historical rainfall data of the Debre Tabor rainfall station for this study, Tests and trends were looked for in the rainfall data. Due to its ability to produce the lowest Akaike, corrected Akaike information criteria, and diagnosis test of goodness of fitness Model Type-MV was chosen for Debre Tabor stations. The parameters of the best models were used to forecast the return levels for each of the following return periods: 2, 5, 10, 25, 50, and 100 years. Because the non-stationary technique has varied intensity levels over time, the annual maximum rainfall from the best appropriate model was calculated using its exceedance probability. Using the 95% of exceedance of the return level, the highest rainfall in each fit was determined. In comparison to the stationary model, the non-stationary model produced higher rainfall intensity values. Therefore, when developing IDF curves, the non-stationary approach should be taken into consideration.

Wave Height Estimation with a Short Return Period

Bisection and grid search methods are proposed as wave height estimation techniques for short return periods (hereafter RP; reference, one year) using long-term wave monitoring data. The proposed method is compared and evaluated with the estimation results using GP (generalized Pareto) and GEV (generalized extreme value) distribution functions, which are widely used as extreme value analysis methods. The wave height data used for the estimation were KMA Ulleungdo Ocean Buoy’s wave height data observed for 12 years from 2012 to 2023. The estimation results show that the annual frequency wave height is 4.55 m, the 90% confidence interval (±5%) is [4.18, 4.69] (m), and the confidence interval for the RP is [0.58, 1.42] (years). The difference from the GP and GEV estimation results (4.61 m and 4.53 m, respectively) was statistically ‘no significance difference.’ The method proposed in this study can estimate design variables for RPs without assumptions on candidate extreme distribution functions or parameter estimation procedures, so it can be used to estimate wave heights for short RPs of one year or less when observation data of approximately ten years or more are available.

Simultaneous lightwave information and power transfer for NLOS ultraviolet communications under different weather conditions

In this work, a power allocation scheme for ultraviolet communication (UVC) with simultaneous lightwave information and power transfer (SLIPT) is proposed. Based on the non-line-of-sight (NLOS) single scattering channel model, the path loss and bit error rate (BER) performance of the UVC system with different geometrical parameters are analyzed. The effects of three types of weather, light rain, fine weather and severe fog conditions are considered. It is proved that the path loss is minimized on foggy days with minimum BER, followed by sunny days. The proposed SLIPT approach that the receiving energy is in turn divided into two parts, one for energy harvesting (EH) and the other for information decoding (ID). The system is designed to optimize energy harvesting for autonomous power supply, while ensuring a specified BER threshold and maintaining spectral efficiency. The effects of three types of weather on the SLIPT system are further investigated. It is demonstrated that under shorter communication distance(r), smaller elevation angle of receiving terminal (βR), larger field of view (FoV) and lower spectral efficiency(η) conditions, a higher percentage of energy is allocated for EH, with foggy days being the most favorable. The extreme geometric parameters of rainy condition can lead to the inability of communication, which needs to be limited to r ≤ 10 m, elevation angle of Rx ≤ 6°, FOV ≥100°, spectral efficiency ≤3, under the preset parameters in this paper.

Investigating impact of unilateral and bilateral femoral anteversion on lower extremity parameters during walking in hypermobile children: A pilot study

Investigating impact of unilateral and bilateral femoral anteversion on lower extremity parameters during walking in hypermobile children: A pilot study

Temperature Extreme Value Evaluation of Composite Beams Based on Copula Functions

The solar temperature field of steel-concrete composite girder bridges has a significant impact on structural stress. To evaluate the distribution of solar temperatures, this paper conducted analyses of the solar temperature field of the Xuefeng Lake Bridge through on-site measurements and numerical simulations. The study investigated the temperature field characteristics of the composite girders according to the temperature data. Based on the numerical simulation results, a finite element computational model for the vertical temperature gradient of the steel-concrete composite girder bridge was established, and the maximum gradient temperature values of the composite girders were calculated by using the 24-year historical data from 2000 to 2023. The extreme value parameters related to the GEV distribution model were determined. Taking into account the correlation between the annual maximum environmental temperature and wind speed, a joint distribution model was established using Copula functions. The results indicate that the average error of the numerical model is within 5%. The wind-temperature joint distribution model, considering the effects of wind speed, tends to provide more conservative results. The calculated extreme values of temperature gradient load show an expanding trend, with the exceedance probabilities for recurrence periods of 100 years, 50 years, 20 years, 10 years, and 5 years being 0.64%, 1.34%, 2.29%, 3.51%, and 7.32%, respectively.

The surrogate model for short-term extreme response prediction based on ANN and Kriging algorithm

Numerical simulation is a common method for calculating the short-term extreme response of floating offshore wind turbines (FOWTs). However, it requires significant computational resources. This study presents a dynamic response database for a 5MW semi-submersible FOWT under complex environmental conditions, including wind speed, effective wave height, and wave spectral peak period, using a numerical model. The peak over threshold (POT) method can be used to obtain the parametric database of short-term extreme responses, which includes the short-term extreme response distribution parameters for four responses: float surge, mooring tension, outward bending moment at the leaf root surface (OoPBM) and tower base pitching moment (TBPM). And the parameter database is applied to train models such as the Genetic Algorithm optimization Back Propagation neural network (GA-BP) and Kriging algorithm models. The research indicates that a correlation can be established between environmental conditions and short-term extreme response parameters using two algorithms. The accuracy of surrogate model prediction for some parameters can be improved by grouping the data based on wind speed and training separately. Additionally, selecting the appropriate surrogate model for each parameter separately can improve the accuracy of short-term extreme response prediction.

Frequency Bias Causes Overestimation of Climate Change Impacts on Global Flood Occurrence

AbstractThe frequency change of 100‐year flood events is often determined by fitting extreme value distributions to annual maximum discharge from a historical base period. This study demonstrates that this approach may significantly bias the computed flood frequency change. An idealized experiment shows frequency bias exceeding 100% for a 50‐year base period. Further analyses using Monte Carlo simulations, mathematical derivations, and hydrological model outputs reveal that bias magnitude inversely relates to base period length and is weakly influenced by the generalized extreme value distribution's shape parameter. The bias, persisting across different estimation methods, implies floods may exceed local defenses designed based on short historical records more often than expected, even without climate change. We introduce a frequency bias adjustment method, which significantly reduces the projected rise in global flood occurrence. This suggests a substantial part of the earlier projected increase in flood occurrence and impacts is not attributable to climate change.

Optimization on parameters of knee airbag considering driver’s instinctive response

Instinctive response was produced for protecting drivers from injury when facing incoming collisions. This study investigated the influence of instinctive response on lower extremity and knee airbag parameters. The change of posture, musculoskeletal characteristic and vehicle control parameters resulting from instinctive response were introduced in injury analysis. The key parameters of knee airbag were optimized based on a multi-object optimization algorithm of response surface method and NSGA-II. Results showed that the increased influence of musculoskeletal characteristic happened when the emergency level varied little. Injury in some cases might increase resulting from the early contact between airbag and lower extremity. It decreased in different levels after the optimization of parameters, with maximum 20%. With the increment of emergency level, the best value of ignition time in the air area, mass-velocity ratio in the brake area and all vent hole ratio increased.

Facile fabrication of THz metasurfaces by a spatially shaped femtosecond laser printing system.

Terahertz (THz) metasurfaces provide unprecedented abilities to realize versatile THz wavefronts manipulations. Nevertheless, these high degree of freedom, non-periodic, densely arranged subwavelength unit cells pose numerous extreme parameter requirements for the fabrication of metasurfaces, presenting significant challenges to their practical application. Herein, a spatial shaping femtosecond laser printing system, based on spatial light modulation (SLM), is proposed for the creation of THz metasurfaces. Through programming the SLM with a sequence of computer-generated holograms (CGH) corresponding to C-shaped Bessel beams with varying opening angles and orientation angles, the C-shaped slit resonant rings with different geometric parameters-fundamental units of the metasurface-were precisely printed onto a gold film. To validate this technique, a THz metalens based on a phased gradient design and a THz holographic plate employing simultaneous phase and amplitude modulation were meticulously fabricated, displaying outstanding performance. Owing to the simple processing flow, high reproducibility, and wide applicability of materials, this technique stands out as a versatile and efficient approach for fabricating THz metasurfaces, with the potential to promote the commercialization of terahertz metasurfaces.

Taxonomic diversity and environmental tolerance of cultivable extremophilic bacteria from a high-altitude meltwater pond on Ojos del Salado (Chile).

Earth harbors unique environments where only microorganisms adapted to extreme conditions, known as extremophiles, can survive. This study focused on a high-altitude meltwater pond, located in the Puna de Atacama, Dry Andes. The extremophilic bacteria of this habitat must adapt to a range of extremities, including cold and dry climate, high UV radiation, high daily temperature fluctuations, low-nutrient availability, and negative water balance. This study aimed to explore the taxonomic diversity of cultivable extremophilic bacteria from sediment samples of a desiccated, high-altitude, meltwater pond using media with different organic matter contents and different incubation temperatures. Based on the 16S rRNA gene sequence analysis, the isolates were identified as members of the phyla Actinobacteria, Proteobacteria, and Firmicutes. The most abundant genera were Arthrobacter and Pseudoarthrobacter. The isolates had oligocarbophilic and psychrotrophic properties, suggesting that they have adapted to the extreme environmental parameters of their natural habitats. The results indicate a positive correlation between nutrient concentration and temperature tolerance.

Seroja Tropical Cyclon Destruction Case Study: Permanent Slope Protection Evaluation at Downstream of Rotiklot Dam Nomenclature Building, East Nusa Tenggara, Indonesia

Abstract Rotiklot Dam was one of some infrastructures which was affected by the Seroja Tropical Cyclone in East Nusa Tenggara Indonesia in April 2021. There are several landslides at the downstream of the dam that can threaten the safety of the dam, especially at the downstream of the nomenclature building. The right design of permanent slope protection must be determined in a limited time. Geotechnical investigations such as boring, resistivity survey, standard penetration test, and water pressure test were conducted in a short time. Back analysis method was carried out to find extreme soil parameters conditions. The slope protection must meet the national standard minimum safety factor or greater than 1.5. Safety factors of slope protections are evaluated by a finite element method to get the safety factor and maximum total displacements. Every stage of slope protection can give the optimal safety factor values which are required or greater than 1.5, however backfill material will give more load and decrease the safety factor value.