Search Results (777)

A systematic sensitivity analysis using three-dimensional discrete element models with discrete fracture networks (DEM-DFN) was conducted to evaluate underground excavation support in jointed rock masses at the CLAB2 site in Southeastern Sweden. The site features a joint network comprising six distinct joint sets, each with unique geometrical properties. The study examined 10 DFNs and 19 rock bolt patterns, both conventional and unconventional. It covered 200 scenarios, including 10 unsupported and 190 supported cases. Technical and economic criteria for stability were assessed for each support system. The results indicated that increasing rock bolt length enhances stability up to a certain point. However, multi-length rock bolt patterns with similar consumption can yield significantly different stability outcomes. Notably, the arrangement and properties of rock bolts are crucial for stability, particularly in blocks between bolting sections. These blocks remain interlocked in unsupported areas due to the induced pressure from supported sections. Although equal-length rock bolt patterns are commonly used, the analysis revealed that triple-length rock bolts (3, 6, and 9 m) provided the most effective support across all ten DFN scenarios. Full article

Quantum sensing based on NV-centers in diamonds has been demonstrated many times in multiple publications. The majority of publications use lasers in free space or lasers with fiber optics, expensive optical components such as dichroic mirrors, or beam splitters with dichroic filters and expensive detectors, such as Avalanche photodiodes or single photon detectors, overall, leading to custom and expensive setups. In order to provide an inexpensive NV-based magnetometer setup for educational use in schools, to teach the three topics, fluorescence, optically detected magnetic resonance, and Zeeman splitting, inexpensive, miniaturized, off-the-shelf components with high reliability have to be used. The cheaper such a setup, the more setups a school can afford. Hence, in this work, we investigated LEDs as light sources, considered different diamonds for our setup, tested different color filters, proposed an inexpensive microwave resonator, and used a cheap photodiode with an appropriate transimpedance amplifier as the basis for our quantum magnetometer. As a result, we identified cheap and functional components and present a setup and show that it can demonstrate the three topics mentioned at a hardware cost <EUR 100. Full article

The 1980 eruption of Mount St. Helens (WA, USA) presented a unique opportunity to observe primary succession in a post-eruption landscape previously dominated by conifer forests. The eruption scoured soil and biological communities adjacent to the mountain, and species of conifers have generally been slow to colonize the nutrient-poor substrate surrounding the volcano. Further, different species of conifer establish and grow at different rates. The recent advancement of conifers in the post-eruption landscape has highlighted a research gap related to conifer growth patterns. We measured the height, age, and incremental growth of 472 trees representing three common conifers, Pseudotsuga menziesii, Abies procera, and Pinus contorta, on debris avalanche (80 sites) and pyroclastic flow (82 sites) disturbance zones of the 1980 eruption. We paired annual incremental growth with recent climate data. We found that height, age, and growth rates differ among species and sites. All species had higher growth rates on the debris avalanche deposit compared to the pyroclastic flow due to either climate or substrate. Climate influences were mixed, where one species increased growth with temperature, another declined, and another was unrelated. Nevertheless, more than 40 years after the eruption, we find rapid height growth in species with implications for future forests. Full article

The performance of optoelectronic devices is affected by various noise sources. A notable factor is the 4.2% lattice mismatch at the Ge/Si interface, which significantly influences the efficiency of Ge-on-Si photodetectors. These noise sources can be analyzed by examining the impact of the Ge/Si interface and deep traps on dark and photocurrents. This study evaluates the impact of these charge traps on key photodetector performance metrics, including responsivity, photo-to-dark current ratio, noise equivalent power (NEP), and specific detectivity (D^*). The trapping effects on charge transport under both forward and reverse bias conditions are monitored through hysteresis analysis. When illuminated with an unmodulated 1550 nm laser, all the key performance metrics exhibit maximum variations at a specific reverse bias. This critical bias marks the transition from saturated to exponential charge transport regimes, where intensified electric fields enhance trap-assisted recombination and thus maximize metric fluctuations. Full article

High-frequency (h. f.) harmonic distortion (HD) of advanced SiGe heterojunction bipolar transistor (HBT)-based power cells (PwCs), featuring optimized metallization interconnections between individual HBTs, was investigated. Single tone input power (P_in) excitations at 1, 2, 5, and 10 GHz frequencies were employed. The output power (P_out) of the fundamental tone and its harmonics were analyzed in both the frequency and time domains. A rapid increase in the third harmonic of P_out was observed at input powers exceeding −8 dBm for a fundamental frequency of 10 GHz in two different PwC technologies. This increase in the third harmonic was analyzed in terms of nonlinear current waveforms, the nonlinearity of the HBT p-n junction diffusion capacitances, substrate current behavior versus P_in, and avalanche multiplication current. To assess the RF power performance of the PwCs, scalar and vectorial load-pull (LP) measurements were conducted and analyzed. Under matched conditions, the SiGe PwCs demonstrated good linearity, particularly at high frequencies. The key power performance of the PwCs was measured and simulated as follows: input power 1 dB compression point (P_{in_1dB}) of −3 dBm, transducer power gain (G_T) of 15 dB, and power added efficiency (PAE) of 50% at 30 GHz. All measured data were corroborated with simulations using the compact model HiCuM L2. Full article

The rapid development of network communication technology has led to an increased focus on the security of image storage and transmission in multimedia information. This paper proposes an enhanced image security communication scheme based on Fibonacci interleaved diffusion and non-degenerate chaotic system to address the inadequacy of current image encryption technology. The scheme utilizes a hash function to extract the hash characteristic values of the plaintext image, generating initial perturbation keys to drive the chaotic system to generate initial pseudo-random sequences. Subsequently, the input image is subjected to a light scrambling process at the bit level. The Q matrix generated by the Fibonacci sequence is then employed to diffuse the obtained intermediate cipher image. The final ciphertext image is then generated by random direction confusion. Throughout the encryption process, plaintext correlation mechanisms are employed. Consequently, due to the feedback loop of the plaintext, this algorithm is capable of resisting known-plaintext attacks and chosen-plaintext attacks. Theoretical analysis and empirical results demonstrate that the algorithm fulfils the cryptographic requirements of confusion, diffusion, and avalanche effects, while also exhibiting a robust password space and excellent numerical statistical properties. Consequently, the security enhancement mechanism based on Fibonacci interleaved diffusion and non-degenerate chaotic system proposed in this paper effectively enhances the algorithm’s resistance to cryptographic attacks. Full article

The estimation of runout distances for long return period avalanches is vital in zoning schemes for mountainous countries. There are two broad methods to estimate snow avalanche runout distance. One involves the use of a physical model to calculate speeds along the incline, with runout distance determined when the speed drops to zero. The second method, which is used here, is based on empirical or statistical models from databases of extreme runout for a given mountain range or area. The second method has been used for more than 40 years with diverse datasets collected from North America and Europe. The primary reason for choosing the method used here is that it is independent of physical models such as avalanche dynamics, which allows comparisons between methods. In this paper, data from diverse datasets are analyzed to explain the relation between them to give an overall view of the meaning of the data. Runout is formulated from nine different datasets and 738 values of extreme runout, mostly with average return periods of about 100 years. Each dataset was initially fit to 65 probability density functions (pdf) using five goodness-of-fit tests. Detailed discussion and analysis are presented for a set of extreme value distributions (Gumbel, Frechet, Weibull). Two distributions had exemplary results in terms of goodness of fit: the generalized logistic (GLO) and the generalized extreme value (GEV) distributions. Considerations included both the goodness-of-fit and the heaviness of the tail, of which the latter is important in engineering decisions. The results showed that, generally, the GLO has a heavier tail. Our paper is the first to compare median extreme runout distances, the first to compare exceedance probability of extreme runout, and the first to analyze many probability distributions for a diverse set of datasets rigorously using five goodness-of-fit tests. Previous papers contained analysis mostly for the Gumbel distribution using only one goodness-of-fit test. Given that climate change is in effect, consideration of stationarity of the distributions is considered. Based on studies of climate change and avalanches, thus far, it has been suggested that stationarity should be a reasonable assumption for the extreme avalanche data considered. Full article

This study presents a hybrid adaptive control strategy that integrates genetic algorithm (GA) optimization with an adaptive neuro-fuzzy inference system (ANFIS) for precise thermal regulation of single-photon avalanche diodes (SPADs). To address the nonlinear and disturbance-sensitive dynamics of SPAD systems, a performance-oriented dataset is constructed through multi-scenario simulations using settling time, overshoot, and steady-state error as fitness metrics. The genetic algorithm (GA) facilitates broad exploration of the proportional–integral–derivative (PID) controller parameter space while ensuring control stability by discarding low-performing gain combinations. The resulting high-quality dataset is used to train the ANFIS model, enabling real-time, adaptive tuning of PID gains. Simulation results demonstrate that the proposed GA-ANFIS-PID controller significantly enhances dynamic response, robustness, and adaptability over both the conventional Ziegler–Nichols PID and GA-only PID schemes. The controller maintains stability under structural perturbations and abrupt thermal disturbances without the need for offline retuning, owing to the real-time inference capabilities of the ANFIS model. By combining global evolutionary optimization with intelligent online adaptation, this approach improves both accuracy and generalization, offering a practical and scalable solution for SPAD thermal management in demanding environments such as quantum communication, sensing, and single-photon detection platforms. Full article

Gallium nitride (GaN) enhancement-mode high-electron-mobility transistors ( E-HEMTs) deliver superior performance compared to traditional silicon (Si) and silicon carbide (SiC) counterparts. Their faster switching speeds, lower on-state resistances, and higher operating frequencies enable more efficient and compact power converters. However, their integration into high-power applications is limited by critical reliability concerns, particularly regarding their short-circuit (SC) withstand capability and overvoltage (OV) resilience. GaN devices typically exhibit SC withstand times of only a few hundred nanoseconds, needing ultrafast protection circuits, which conventional desaturation (DESAT) methods cannot adequately provide. Furthermore, their high switching transients increase the risk of false activation events. The lack of avalanche capability and the dynamic nature of GaN breakdown voltage exacerbate issues related to OV stress during fault conditions. Although SC-related behaviour in GaN devices has been previously studied, a focused and comprehensive review of protection strategies tailored to GaN technology remains lacking. This paper fills that gap by providing an in-depth analysis of SC and OV failure phenomena, coupled with a critical evaluation of current and next-generation protection schemes suitable for GaN-based high-power converters. Full article

Axis definition plays a key role in the establishment of animal body plans, both in normal development and regeneration. The cnidarian Hydra can re-establish its simple body plan when regenerating from a random cell aggregate or a sufficiently small tissue fragment. At the beginning of regeneration, a hollow cellular spheroid forms, which then undergoes symmetry breaking and de novo body axis definition. In the past, we have published related work in a physics journal, which is difficult to read for scientists from other disciplines. Here, we review our work for readers not so familiar with this type of approach at a level that requires very little knowledge in mathematics. At the same time, we present a few aspects of Hydra biology that we believe to be linked to our work. These biological aspects may be of interest to physicists or members of related disciplines to better understand our approach. The proposed theoretical model is based on fluctuations of gene expression that are triggered by mechanical signaling, leading to increasingly large groups of cells acting in sync. With a single free parameter, the model quantitatively reproduces the experimentally observed expression pattern of the gene ks1, a marker for ‘head forming potential’. We observed that Hydra positions its axis as a function of a weak temperature gradient, but in a non-intuitive way. Supposing that a large fluctuation including ks1 expression is locked to define the head position, the model reproduces this behavior as well—without further changes. We explain why we believe that the proposed fluctuation-based symmetry breaking process agrees well with recent experimental findings where actin filament organization or anisotropic mechanical stimulation act as axis-positioning events. The model suggests that the Hydra spheroid exhibits huge sensitivity to external perturbations that will eventually position the axis. Full article

With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake, located in the southeastern part of the Tibetan Plateau, using an integrated approach combining remote sensing, field surveys, and numerical modeling. Results show that the lake has expanded significantly—from 2.08 km² in 1990 to 5.43 km² in 2021—with the most rapid increase observed between 2015 and 2016. InSAR data and optical imagery indicate that surrounding moraine deposits remain generally stable. However, ice avalanches from the glacier terminus are identified as the primary trigger for lake outburst via wave-induced overtopping. Mechanical and geomorphological analyses suggest that the moraine dam is resistant to downcutting erosion, reinforcing overtopping as the dominant failure mode. To assess potential impacts, three numerical simulation scenarios were conducted based on different avalanche volumes. Under the extreme scenario involving a 5-million m³ ice avalanche, the modeled peak discharge at the dam site reaches approximately 19,000 m³/s. Despite the high flood magnitude, the broad and gently sloped downstream terrain facilitates rapid attenuation of flood peaks, resulting in limited impact on downstream settlements. These findings offer critical insights for GLOF hazard assessment, disaster preparedness, and risk mitigation under a changing climate. Full article

We develop a symmetry-based variational theory that shows the coarse-grained balance of work inflow to heat outflow in a driven, dissipative system relaxed to the golden ratio. Two order-2 Möbius transformations—a self-dual flip and a self-similar shift—generate a discrete non-abelian subgroup of $\mathrm{PGL}(2,\mathbb{Q}\left(\sqrt{5}\right))$. Requiring any smooth, strictly convex Lyapunov functional to be invariant under both maps enforces a single non-equilibrium fixed point: the golden mean. We confirm this result by (i) a gradient-flow partial-differential equation, (ii) a birth–death Markov chain whose continuum limit is Fokker–Planck, (iii) a Martin–Siggia–Rose field theory, and (iv) exact Ward identities that protect the fixed point against noise. Microscopic kinetics merely set the approach rate; three parameter-free invariants emerge: a $62\%:38\%$ split between entropy production and useful power, an RG-invariant diffusion coefficient linking relaxation time and correlation length ${\mathcal{D}}_{\alpha }={\xi }^z/\tau$, and a $\vartheta ={45}^{\circ }$ eigen-angle that maps to the golden logarithmic spiral. The same dual symmetry underlies scaling laws in rotating turbulence, plant phyllotaxis, cortical avalanches, quantum critical metals, and even de-Sitter cosmology, providing a falsifiable, unifying principle for pattern formation far from equilibrium. Full article

Laser ranging technology holds a key position in the military, aerospace, and industrial fields due to its high precision and non-contact measurement characteristics. As a core component, the performance of the photon detector directly determines the ranging accuracy and range. This paper systematically reviews the technological development of photonic detectors for laser ranging, with a focus on analyzing the working principles and performance differences of traditional photodiodes [PN (P-N junction photodiode), PIN (P-intrinsic-N photodiode), and APD (avalanche photodiode)] (such as the high-frequency response characteristics of PIN and the internal gain mechanism of APD), as well as their applications in short- and medium-range scenarios. Additionally, this paper discusses the unique advantages of special structures such as transmitting junction-type and Schottky-type detectors in applications like ultraviolet light detection. This article focuses on photon counting technology, reviewing the technological evolution of photomultiplier tubes (PMTs), single-photon avalanche diodes (SPADs), and superconducting nanowire single-photon detectors (SNSPDs). PMT achieves single-photon detection based on the external photoelectric effect but is limited by volume and anti-interference capability. SPAD achieves sub-decimeter accuracy in 100 km lidars through Geiger mode avalanche doubling, but it faces challenges in dark counting and temperature control. SNSPD, relying on the characteristics of superconducting materials, achieves a detection efficiency of 95% and a dark count rate of less than 1 cps in the 1550 nm band. It has been successfully applied in cutting-edge fields such as 3000 km satellite ranging (with an accuracy of 8 mm) and has broken through the near-infrared bottleneck. This study compares the differences among various detectors in core indicators such as ranging error and spectral response, and looks forward to the future technical paths aimed at improving the resolution of photon numbers and expanding the full-spectrum detection capabilities. It points out that the new generation of detectors represented by SNSPD, through material and process innovations, is promoting laser ranging to leap towards longer distances, higher precision, and wider spectral bands. It has significant application potential in fields such as space debris monitoring. Full article

Snow-dominated watersheds experience a snowmelt-driven peak in streamflow that occurs in the spring or early summer. Some of the headwater basins in Colorado, USA have two or more peaks in streamflow, including the Uncompahgre River, a Colorado River tributary. The timing of peak streamflow is important for water management and recreational planning. As such, we examined the connection between the timing of each streamflow peak and readily available snow measurement information in the forest and alpine zones. These station data are the date of the initiation of snowmelt, 50% melt-out, and complete melt-out or the snow disappearance date (SDD). When it occurs before mid-June (14 of 20 years), the timing of the first peak is well correlated with the forested snow measurement station SDD. The second streamflow peak timing is well correlated with SDD from the alpine station except for very early (3 years) and very late (2 years) SDD. We also examine the spatial variability of snow disappearance and peak snow water equivalent (SWE) across the four seasonally snow-covered headwater sub-basins using a dataset from a coupled meteorological–snowpack model. Full article

Investigating avalanche hazards is a fundamental preliminary task in avalanche research. This work is critically important for establishing avalanche warning systems and designing mitigation measures. Primary research data originated from field investigations and UAV aerial surveys, with avalanche counts and timing identified through image interpretation. Snowpack properties were primarily acquired via in situ field testing within the study area. Methodologically, statistical modeling and RAMMS::AVALANCHE simulations revealed spatiotemporal and dynamic characteristics of avalanches. Subsequent application of the Certainty Factor (CF) model and sensitivity analysis determined dominant controlling factors and quantified zonal influence intensity for each parameter. This study, utilizing field reconnaissance and drone aerial photography, identified 86 avalanche points in the study area. We used field tests and weather data to run the RAMMS::AVALANCHE model. Then, we categorized and summarized regional avalanche characteristics using both field surveys and simulation results. Furthermore, the Certainty Factor Model (CFM) and the parameter Sensitivity Index (Sa) were applied to assess the influence of elevation, slope gradient, aspect, and maximum snow depth on the severity of avalanche disasters. The results indicate the following: (1) Avalanches exhibit pronounced spatiotemporal concentration: temporally, they cluster between February and March and during 13:00–18:00 daily; spatially, they concentrate within the 2100–3000 m elevation zone. Chute-confined avalanches dominate the region, comprising 73.26% of total events; most chute-confined avalanches feature multiple release areas; therefore the number of release areas exceeds avalanche points; in terms of scale, medium-to-large-scale avalanches dominate, accounting for 86.5% of total avalanches. (2) RAMMS::AVALANCHE simulations yielded the following maximum values for the region: flow height = 15.43 m, flow velocity = 47.6 m/s, flow pressure = 679.79 kPa, and deposition height = 10.3 m. Compared to chute-confined avalanches, unconfined slope avalanches exhibit higher flow velocities and pressures, posing greater hazard potential. (3) The Certainty Factor Model and Sensitivity Index identify elevation, slope gradient, and maximum snow depth as the key drivers of avalanches in the study area. Their relative impact ranks as follows: maximum snow depth > elevation > slope gradient > aspect. The sensitivity index values were 1.536, 1.476, 1.362, and 0.996, respectively. The findings of this study provide a scientific basis for further research on avalanche hazards, the development of avalanche warning systems, and the design of avalanche mitigation projects in the study area. Full article