Field Monitoring Research Articles

Identifying failure connection area on wall for deep excavation based on system stiffness influence factor

In this study, a methodology to identify weak or failure connection area on the wall of deep excavation was proposed based on the system stiffness influence factor (IF), which can be beneficially utilized for wall-collapse prevention and forecasting system. Irregular excavation configuration common in urban areas and various weak-connection locations were considered. Three-dimensional finite element analyses with full consideration of actual staged excavation and strut-waler connection condition were performed. It was found that wall deflection and ground movement increased as the location of weak connection became deeper. It was also found that the influence of weak connection on the wall behavior became more pronounced as it located towards the center of the wall. The effects of weak connection on wall deflection were evaluated and quantified using IF. A modification procedure for IF was introduced to consider the effects of depth and horizontal weak-connection locations. The modified IF was adopted to establish a method for quantifying and identifying weak or failure connection area on the wall based on measured wall deflection from field monitoring. Case examples were selected to check the validity of the proposed method. The compared results showed that monitored and predicted locations of weak connection were in close agreement.

Precision Medicine in Peritoneal Dialysis: An Expert Opinion on the Application of the Sharesource Platform for the Remote Management of Patients.

The management of end-stage kidney disease (ESKD) has been constantly evolving over the last decade with the development of targeted approaches. In this field, telemedicine and remote monitoring are based on the availability of new cyclers that allow for bidirectional communication (between patient and physician) and for the application of the Sharesource cloud-based platform. These technologies allow patients with ESKD to undergo automated peritoneal dialysis (APD) at home. However, these approaches are not well standardized and largely applied yet. Therefore, this study aimed to elaborate a protocol for the utilization of the Sharesource platform to facilitate the practical management of patients treated with APD. A series of expert meetings were held between September 2022 and January 2023 in Italy. The participants (ten nephrologists and five nurses) from nine Italian public dialysis centers shared their opinions, examined the current scientific literature in the field, and reviewed the key characteristics of the Sharesource system to achieve a common position on this topic. A detailed and practical document containing experts' opinions and suggestions on the use of the Sharesource platform for the management of patients treated with APD was produced. This expert opinion might represent a new useful instrument in clinical practice for managing patients undergoing home-based peritoneal dialysis (PD) through the Sharesource platform, which is valid not only for Italy. These recommendations pave the way to novel patient-centered and personalized therapeutic approaches for ESKD and highlight the advantages of telemedicine and remote monitoring in the management of patients with ESKD undergoing PD and its positive impact on their quality of life.

Effects of mixed land use on urban stormwater quality under different rainfall event types

The joint effect of mixed land uses and rainfall event types was studied using a two-year field monitoring program in four urban catchments in Calgary, Alberta, Canada. Event mean concentration (EMC) and event pollutant load (EPL) were employed to evaluate the total suspended sediment (TSS), nitrogen and phosphorus. The correlation analysis showed that most nitrogen and phosphorus components (except for NO2−/NO3− and TDP) predominantly exist in particulate form in the study areas. The correlation for EPL was notably stronger than EMC, which can be attributed to varying rainfall characteristics. The differences in EMCs and EPLs of TSS, nitrogen and phosphorus across catchments indicated that the complexity and spatial distribution of mixed land use can influence the generation and transportation of pollutants in urban runoff. The impacts of rainfall characteristics on stormwater quality are integrated rather than driven by a single rainfall characteristic. Brief but intense events tended to elevate TSS, nitrogen and phosphorus concentrations, especially in complex land-use catchments. Events with long antecedent dry days and short duration also resulted in increased pollutant concentrations, while events with long duration and low intensity could result in higher EPLs. The effect of mixed land use on water quality can vary depending on rainfall event types. Seasonal variations were found in EMC and EPL of TSS, nitrogen and phosphorus, with higher values in the spring and summer than the fall. Seasonal variations are mainly influenced by rainfall conditions, temperature and anthropogenic activities (e.g. lawn fertilization and de-icing with sands). MLR considering rainfall characteristics is an effective method for predicting stormwater quality within a single catchment. Considering complexity and spatial distribution of mixed land use can improve the accuracy of the harmonized MLR model. This research provided insights into understanding the complexities introduced by mixed land use and rainfall event types in urban stormwater quality.

Variation of segment joint opening of underwater shield tunnel during long operational period

Segment joint is the main water leakage channel in underwater shield tunnels, and joint deformation influences tunnel waterproof capacity greatly. Real-time structure health monitoring is a great way to investigate the joint opening and to offer early warnings for abnormality, such as data outlier and joint properties degradation. This study investigated the variation of joint opening, provided early warning indexes and evaluated the joint mechanical properties degradation using the field monitoring data of an underwater shield tunnel over 10 years, which is rarely seen in the literature. Study results show that: (1) Field monitoring data reveals that the distribution of joint opening increments obeys a heavy-tailed distribution rather than the normal distribution. The exponential distribution model and the log normal distribution model can fit the longitudinal joint increments and circumferential joint increments much better. (2) The early warning index is determined based on the statistic theory and 0.999 quantile is set as the warning value. The obtained warning values of the studied underwater tunnel are 0.005 mm and 0.08 mm for the longitudinal and circumferential joint respectively. The small warning value means that small abnormality can be identified and the early warning would be more efficient. (3) A mechanical model is proposed to evaluate the joint mechanical properties degradation based on monitoring data. Results show that normal stiffness of circumferential joint decreases from 18.3 GPa/m to 14.7 GPa/m. Results of this study provides valuable reference for early-warning and joint degradation evaluation of under water shield tunnel.

In-Fiber Hybrid Structure Sensor Based on the Vernier Effect for Vector Curvature and Temperature Measurement

A vector curvature and temperature sensor based on an in-fiber hybrid microstructure is proposed and experimentally demonstrated. The proposed scheme enables the dimensions of the Fabry–Perot and Mach–Zehnder hybrid interferometer to be adjusted for the formation of the Vernier effect by simply changing the length of a single optical fiber. The sensor is fabricated using a fiber Bragg grating (FBG), multimode fiber (MMF), and a single-hole dual-core fiber (SHDCF). The sensor exhibits different curvature sensitivities in four vertical directions, enabling two-dimensional curvature sensing. The temperature and curvature sensitivities of the sensor were enhanced to 100 pm/°C and −25.55 nm/m−1, respectively, and the temperature crosstalk was minimal at −3.9 × 10−3 m−1/°C. This hybrid microstructure sensor technology can be applied to high-sensitivity two-dimensional vector curvature and temperature detection for structural health monitoring of buildings, bridge engineering, and other related fields.

Applying Theory of Change in research program planning: Lessons from CGIAR

Theory of Change (ToC) is widely used as a tool to support strategic planning, monitoring, and evaluation in many fields, especially for social and environmental programs. However, there is still limited documented experience with the application and use of ToC in a research context. CGIAR, a global network of 15 centers conducting international research-for-development, included a standardized ToC approach in a recent round of developing 32 large research Initiatives. This unique experience offers an ideal opportunity to learn from organization-scale ToC implementation and use. The paper provides an overview of research-for-development challenges and ToC concepts and a brief history of ToC use in CGIAR. We describe the application of ToC in this recent case and then assess strengths and weaknesses of the process and the ToCs developed as part of the Initiative proposals. CGIAR made important advances in standardizing ToC concepts and terminology, tools, and guidance, and in integrating ToC into annual reporting and evaluation. Nevertheless, many of the ToCs were insufficiently clear and specific, with substantial scope for further improvement. This is due in part to the rushed and decentralized proposal development process, undertaken during pandemic restrictions, but also reflects different mental-models of research-for-development processes and gaps in understanding and capacity. Recommendations to improve development and use of ToC include capacity development in conceptualizing research impact pathways, ensuring that research design teams have a dedicated M&E specialist paying particular attention to ToCs, improved ToC templates, and better accountability for ToC development and use over the life of a program.

Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion

Defects in Laser Powder Bed Fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. Experimental in-situ monitoring of the three-dimensional melt pool physical fields is challenging, due to the short length and time scales involved in the process. Multi-physics simulation methods can describe the three-dimensional dynamics of the melt pool, but are computationally expensive at the mesh refinement required for accurate predictions of complex effects. Therefore, we develop a generative deep learning model based on the probabilistic diffusion framework to map low-fidelity simulation information to the high-fidelity counterpart. By doing so, we bypass the computational expense of conducting multiple high-fidelity simulations for analysis by upscaling lightweight coarse mesh simulations. We demonstrate the preservation of key metrics of the melting process between the ground truth simulation data and the diffusion model output, such as the temperature field, the melt pool dimensions and the variability of the keyhole vapor cavity. We predict the melt pool depth within 3 μm based on low-fidelity input data 4× coarser than the high-fidelity simulations, reducing analysis time by two orders of magnitude.

Geochemical drivers of manganese removal in drinking water reservoirs under hypolimnetic oxygenation

Manganese (Mn) is a naturally occurring contaminant commonly found in drinking water supplies. In lakes and reservoirs, water authorities increasingly use in situ treatment by hypolimnetic oxygenation (HOx) systems to remove metals such as Mn from the water column. HOx systems introduce dissolved oxygen (DO) to the bottom waters (hypolimnion) to promote oxidation and subsequent removal of metals from the water column. Previous laboratory studies have shown the importance of individual geochemical drivers (pH, alkalinity, mineral surfaces) on Mn oxidation, but few studies have examined the influence of these drivers of Mn removal in concert. In this study, we conducted field monitoring and laboratory experiments to examine how pH, alkalinity and the presence of mineral particles influence Mn removal at two drinking water reservoirs in southwest Virginia, both with HOx systems: Falling Creek Reservoir (FCR) and Carvins Cove Reservoir (CCR). Both reservoirs have had historical issues with elevated (>0.05 mg/L) Mn concentrations during seasonal stratification (May–October). Watershed geology contributes to differences in pH and alkalinity between the reservoirs, with FCR having lower historical medians of hypolimnetic pH and alkalinity (6.6 and 18 mg/L CaCO3, respectively) than CCR (7.2 and 62 mg/L CaCO3, respectively).Results of laboratory experiments examining the influence of pH on Mn removal showed substantial Mn loss within 14 days only under high pH (10) conditions. Mn removal did not occur at pH 6 or 8 over the same 14-day period. In experiments with pH 10 and alkalinity >70 mg/L CaCO3, near-total Mn removal occurred within 2 h. Mn removal occurred concurrently with precipitation of microscopic (<5 μm) particles, followed by formation of macroscopic (>100 μm) particles. Particles of both size classes were identified as Mn oxides (MnOx). These observations suggest that increasing pH and alkalinity promotes Mn oxidation and subsequent removal from solution. Results of experiments with pH 10 and alkalinity >70 mg/L CaCO3 suggest that heterogeneous oxidation by MnOx partially drives rapid Mn removal. Thus, initial formation of MnOx creates a positive feedback loop that can enhance additional Mn loss. In experiments using water collected from FCR and CCR, we observed rapid Mn removal in unfiltered water (0.002–0.05 d−1) but no significant removal of Mn in filtered water. These results, in combination with results of analysis of particles collected from reservoir water, suggest that minerals present in the water column likely catalyze MnOx formation. Together, our experimental results suggest that heterogenous oxidation is an important process of Mn removal, while pH and alkalinity variations of the range expected in natural freshwaters contribute less to differential Mn removal. The formation of MnOx particles during in situ oxygenation, as well as the presence of suspended minerals that occur naturally in water columns, play an important role in promoting Mn oxidation and should be accounted for in Mn removal treatment strategies.

Stress-strain state zoning model and novel large deformation classification method for squeezing tunnels

Accurately assessing the level of large deformation in squeezing tunnels is of great importance for the design of support structures. The current large deformations classification methods fail to account for the effect of support pressure on the relative deformation of surrounding rock. In this study, a theoretical model for the stress–strain state zoning of the surrounding rock in squeezing tunnels is established. A sensitivity analysis of the model parameters is conducted. The distribution law of the strength-stress ratio, relative deformation, and relative support pressure indices in 43 field monitoring squeezing tunnels are statistically analyzed. A novel large-deformation classification method based on the relative support pressure index is proposed and applied in case studies. The parameter sensitivity analysis shows that mechanical parameters of the surrounding rock significantly affect the deformation and the stress–strain state zoning of the surrounding rock. The stress–strain state zoning and deformation of the surrounding rock are also primarily dependent on the matching relationship between strength-stress ratio and support pressure. Statistical analyses indicate that there is a nonlinear negative correlation between the relative deformation of the surrounding rock and the strength-stress ratio, as well as the relative support pressure, which includes the steel arch relative support pressure index (SSPI) and the anchor bolt relative support pressure Index (ASPI). The key to controlling surrounding rock deformation lies in the rational matching of support pressure to the strength-stress ratio. In the novel large deformation classification method, three key indexes of strong stress ratio, relative deformation and relative support pressure are quantitatively included, and squeezing large deformation is divided into three levels. Moreover, the case study demonstrated that the novel large deformation classification method has significant guiding importance in verifying feasibility and optimizing support design schemes during both the design and construction phases.

Excavation Method Comparison and Optimization for a Super Large Cross-Section Tunnel

Characterized by long spans, low aspect ratios, and intricate construction sequences, super-large cross-section tunnels present substantial construction risks. Therefore, the selection of the optimal excavation method and construction sequence is crucial for ensuring the safety of tunnel construction and minimizing project costs. This paper takes a super large transverse-section highway tunnel as a case study, employing field monitoring data combined with ABAQUS software to analyze the stress and deformation of surrounding rock and support structures under different excavation methods. The findings reveal that the deformation of surrounding rock and support structures excavated by the Double-Side Drift Method is smaller than those caused by the three-benching seven-step method and the CRD excavation method. Nevertheless, the significant stresses of surrounding rock and support structures are released by the Double-Side Drift Method, leading to potential stress concentrations. Thus, it is necessary to ensure the rapid completion of early support and quick sealing of the tunnel. Furthermore, the sixth process achieves smaller deformation (including arch displacement and surface settlement) of the tunnel, a shorter construction period, and lower economic costs when compared to other construction processes. Consequently, it can obviously be concluded that both the Double-Side Drift Method and the sixth construction process stand out as the most appropriate choices for excavating super large cross-section tunnels. The insights obtained from this study provide theoretical guidance for the design and construction of similar tunnel projects.

Research on Microclimate Optimization of Traditional Residential Buildings in Central Anhui Based on Humid and Hot Climate Characteristics and Regional Architectural Features

This study examines how building space, materials, and structure affect the microclimate of Liu Tong Xinglongzhuang in central Anhui, known for its hot, humid climate and distinct architecture. Using qualitative and quantitative methods, including field monitoring, PHOENICS simulation, and Ladybug Tools, the following conclusions were drawn: (1) Building materials: wood reduces indoor temperature; a glass roof over the patio lowers temperature and improves wind speed; and reducing tile area decreases solar radiation. (2) Building space: optimal comfort in stairwells is achieved with a length-to-width ratio of 1.5:1 and height-to-width ratio of 2:1; courtyards are most comfortable with a length-to-width ratio of 2.5:1 and height-to-width ratio of 1.5:1; walk-through halls are optimal with a length-to-width ratio of 2:1 and height-to-width ratio of 1.5:1; and wings achieve the highest comfort with a length-to-width ratio of 2.5:1 and height-to-width ratio of 1.5:1. (3) Building structure: optimal wind speed and temperature are achieved with specific window height-to-width ratios of 1:1 for exterior and 1.5:1 for interior windows; the lowest temperatures occur at 2:1 ratios; hexagonal exterior and circular interior windows maximize wind speed and temperature reduction; and smaller exterior door openings lower indoor temperatures and are best achieved with an interior door ratio of 2:1. These findings offer valuable data and methods for optimizing the microclimate of traditional houses, with significant practical implications.

Eco-friendly fluorescent detection method for Cu2+ ions combined with smartphone-integrated paper strip sensors based on highly fluorescent 2-aminoterephthalic acid in milk samples

The creation of smart, real-time sensing devices is crucial in food monitoring, though it continues to be a major challenge. Here, we report an eco-friendly fluorescent detection method for Cu2+ ions using 2-aminoterephthalic acid (NH2-H2BDC). Fluorescence (FL) quenching occurs at 425 nm under excitation at 330 nm, with detection limits (LOD) as low as 16.25 nM for Cu2+ ions. Additionally, a smartphone can visually and quantitatively detect Cu2+ ions by analyzing the RGB values on test paper. The results show high sensitivity, with a LOD of 11.07 μM. This work not only reveals fluorescent detection methods but also develops a convenient, low-cost, and portable smartphone-integrated paper strip for Cu2+ ion sensing. Two metrics, AGREEprep and BAGI, were employed to assess the method's environmental friendliness. The evaluation confirmed its exceptional eco-friendliness. This method marks a significant advancement for Cu2+ ion monitoring in diverse fields, especially food monitoring.

Field Observation and Settlement Prediction Study of a Soft Soil Embankment under Rolling Dynamic Compaction

Rolling dynamic compaction (RDC) has been found to be useful for compaction soils and is now widely used globally. Because RDC is not often used in soft soils with poor engineering properties, field monitoring was used to study the soft clay embankment responses under RDC conditions in this study. Analysis of the monitoring data revealed that the response of the soil occurred mainly in the first 20 passes. Field monitoring revealed a strong correlation between settlement, horizontal displacement, and pore water pressure. The depth of impact of RDC on the soft soil embankment was between 3 and 3.5 m. Although settlement prediction is an important issue for construction, there is a lack of prediction methods for RDC-induced soil settlement. In this study, we used three different machine learning algorithms: random forest regression (RFR), multilayer perceptron (MLP), and extreme gradient boosting (XGBoost) to predict the total settlement and uneven settlement induced by RDC on the soft soil embankment. The three prediction models were compared, and the predictive accuracy of these models was assessed. This study analyzes and summarizes the effect of RDC application on a soft clay embankment and explores the machine learning method used for settlement prediction based on monitoring data, which provides some methods and ideas for research on the application of RDC on soft soil foundations.

Life cycle, host specificity and potential impact of a gall-inducing thrips Acaciothrips ebneri, a biological control agent for prickly acacia (Vachellia nilotica subsp. indica) in Australia

Prickly acacia (Vachellia nilotica subsp. indica (Benth.) Kyal. & Boatwr.; Fabales: Fabaceae) is a Weed of National Significance and a target for biological control in Australia. Currently there are no effective biological control agents for the weed in Australia. Based on genetic and climate matching, a gall thrips (Acaciothrips ebneri Karny; Thysanoptera: Phlaeothripidae) inducing rosette galls resulting in shoot tip dieback, was identified as a prospective biological control agent from Ethiopia. No-choice host-specificity tests were conducted on 59 test plant species in a high security quarantine in Brisbane, Australia. Acaciothrips ebneri is host-specific, inducing galls and reproducing only on prickly acacia. Acaciothrips ebneri, as predicted by the CLIMEX model, is suited to hot and arid western Queensland where major prickly acacia infestations occur. The Australian Government approved A. ebneri for field release in October 2022. This is the first time a true gall-inducing thrips has ever been approved as a weed biological control agent. Field releases commenced in January 2023 and are in progress. There are early signs of field establishment resulting in shoot tip die back in the field, and field release and monitoring will continue.

Leveraging camera traps and artificial intelligence to explore thermoregulation behaviour.

Behavioural thermoregulation has critical ecological and physiological consequences that profoundly influence individual fitness and species distributions, particularly in the context of climate change. However, field monitoring of this behaviour remains labour-intensive and time-consuming. With the rise of camera-based surveys and artificial intelligence (AI) approaches in computer vision, we should try to build better tools for characterizing animals' behavioural thermoregulation. In this study, we developed a deep learning framework to automate the detection and classification of thermoregulation behaviour. We used lizards, the Rough-tail rock agama (Laudakia vulgaris), as a model animal for thermoregulation. We colour-marked the lizards and curated a diverse dataset of images captured by trail cameras under semi-natural conditions. Subsequently, we trained an object-detection model to identify lizards and image classification models to determine their microclimate usage (activity in sun or shade), which may indicate thermoregulation preferences. We then evaluated the performance of each model and analysed how the classification of thermoregulating lizards performed under different solar conditions (sun or shade), times of day and marking colours. Our framework's models achieved high scores in several performance metrics. The behavioural thermoregulation classification model performed significantly better on sun-basking lizards, achieving the highest classification accuracy with white-marked lizards. Moreover, the hours of activity and the microclimate choices (sun vs shade-seeking behaviour) of lizards, generated by our framework, are closely aligned with manually annotated data. Our study underscores the potential of AI in effectively tracking behavioural thermoregulation, offering a promising new direction for camera trap studies. This approach can potentially reduce the labour and time associated with ecological data collection and analysis and help gain a deeper understanding of species' thermal preferences and risks of climate change on species behaviour.

Study on Deformation Control of Road-Deep Foundation Pit Passing under Elevated Subway Bridge

This paper focuses on the application of pile foundation underpinning technology in a deep foundation pit of a subway Viaduct Project in Beijing. The study aims to address the engineering characteristics of the project, including a large number of new piles, a wide span of underpinning abutment, a long length of deep foundation pit, and a wide range of influences. This research utilizes field monitoring and numerical simulation methods to investigate the pile foundation underpinnings. The impact and management of road-deep foundation pit construction are considered, as well as their combined effect on subway viaducts and track structures. The primary accomplishments are as follows: (1) By analyzing the data from on-site deformation monitoring, it is evident that the pier exhibits maximum vertical deformation and maximum transverse deformation at the same location. The measuring locations are specifically situated on Pier 7# at the pile foundation underpinning. The maximum vertical and transverse deformations of the track are directly proportional to the maximum deformation of the pier. (2) By comparing the numerical simulation results with the field monitoring data, it is observed that although there is some discrepancy between the two, the deformation trend is largely consistent. This suggests that the numerical simulation analysis method is effective in reflecting the deformation of the bridge and track. (3) Through the numerical model and changing the values of the retaining structure parameters, the sensitivity of the pier deformation near the road foundation pit to the retaining structure parameters is systematically analyzed. The sensitivity of the pier deformation to the foundation pit parameters is as follows: the embedded depth insertion ratio of the retaining pile &gt; the diameter of the retaining pile &gt; the pile spacing.

Integrated approach of predicting rock stability in high mountain valley underground caverns

High mountain valleys are characterized by the development of intricate ground stress fields due to geological processes such as tectonic stress, river erosion, and rock weathering. These processes introduce considerable stability concerns in the surrounding rock formations for underground engineering projects in these regions, highlighting the imperative need for rigorous stability assessments during the design phase to ensure construction safety. This paper introduces an innovative approach for the pre-evaluation of the stability of surrounding rocks in underground caverns situated within high mountain valleys. The methodology comprises several pivotal steps. Initially, we conduct inverse calculations of the ground stress field in complex geological terrains, combining field monitoring and numerical simulations. Subsequently, we ascertain stress-strength ratios of the surrounding rocks using various rock strength criteria. To assess the stability characteristics of the surrounding rocks in the 1# spillway cave within our project area, we employ numerical simulations to compute stress-strength ratios based on different rock strength criteria. Furthermore, we undertake a comparative analysis, utilizing data from the 5# Underground Laboratory (Lab 5) of Jinping II Hydropower Station, aligning the chosen rock strength criterion with the damage characteristics of Lab 5′s surrounding rocks. This analysis serves as the cornerstone for evaluating other mechanical responses of the surrounding rocks, thereby validating the pre-evaluation methodology. Our pre-evaluation method takes into account the intricate geological evolution processes specific to high mountain valleys. It also considers the influence of the initial geostress field within the geological range of underground caverns. This comprehensive approach provides a robust foundation for the analysis and assessment of the stability of surrounding rocks, especially in high mountain valley areas, during the design phase of underground engineering projects. The insights derived from this analysis hold substantial practical significance for the effective guidance of such projects.

Developing a habitat suitability index with field data and hydraulic models

AbstractLinking habitat availability with hydraulic models integrates river engineering in the ecological field. Field observation for species presence and physical habitat availability mapping is inherently limited due to time and access constraints for field data collection. This study leverages hydraulic modeling to supplement larval fish population monitoring data, effectively expanding mapped physical habitat and allowing for monitoring bias analysis. The inundation extents and character of streamflow from hydraulic modeling were used to refine habitat suitability indices relative to total habitat availability from discrete fish monitoring events. Given the flexibility in hydraulic modeling to simulate a range of flows, the habitat suitability index is then translated to an effective habitat curve according to areal inundation and hydrologic frequency. With this framework, forecasting the impacts of long‐term trends, such as geomorphic or hydrologic change, can be reasonably and quantitatively assessed. This manuscript uses a case study of Rio Grande silvery minnow monitoring at restoration sites where the floodplain has been lowered via earthwork. Comparisons are made for habitat suitability indices developed from field observation data alone and field observation supplemented by hydraulic modeling. Known biases of field sampling data (targeting slow, shallow areas where fish are most often found) were confirmed based on simulated hydraulic conditions across entire restoration sites. In the case of Rio Grande silvery minnow, a heavily studied species, such field monitoring biases are an effective use of resources. However, this framework may be helpful for assessing alternative management approaches and monitoring strategies of species that are less studied.

The pressure field model: a challenge to the conventional Starling and Guyton model of hemodynamic management

IntroductionEnsuring hemodynamic stability with adequate perfusion to vital organs is critical to the safe conduct of anesthesia. Recent advances in hemodynamic monitoring technologies allow pressure, flow, and resistance to be measured continuously; however, there is limited evidence to suggest that these technologies alter clinical management or improve patient outcomes significantly. This may be because the fundamental hemodynamic model, established by Starling and Guyton, fails to offer the granular level of insight needed to guide clinical management.MethodsWe collected hemodynamic data from 950 patients who underwent major surgery with advanced hemodynamic monitoring (AHM) that provided continuously derived cardiac output and vascular resistance measurements. These measurements were based on the hemodynamic model of Starling and Guyton. Additionally, investigational monitoring software was developed to visualize a different hemodynamic model, termed the “pressure field” model. This model expresses the pulsatile, beat-to-beat relationship between ventricular performance (measured by stroke volume) and vascular tone (indicated by systemic elastance).ResultsWithin this dataset were several patients who experienced major hemorrhage. Case studies of these patients demonstrate that abnormal pressure and flow regulation patterns are observed through the lens of the pressure field model, but these patterns are typically not visible through the lens of the traditional Starling and Guyton model (cardiac output and systemic vascular resistance, which involve averaging hemodynamic performance over successive cardiac cycles). Furthermore, “before and after” case studies using our investigational pressure field monitoring software suggest that the traditional Starling and Guyton hemodynamic model has limited utility in managing hemorrhage.DiscussionWe propose that the pressure field model may allow hemorrhage to be managed more effectively via improved monitoring granularity [the beat-by-beat visualization of the stroke volume-systemic elastance relationship, rather than the use of the composite metrics of cardiac output (heart rate × stroke volume) and systemic vascular resistance]. Further research into the utility of the pressure field model is warranted.

Comfort assessment of wind induced vibrations for slender structures by field monitoring and numerical analysis

Slender structures often lead to vibration discomfort for occupants when exposed to wind forces. This study proposes an innovative method for assessing comfort against wind-induced vibrations for slender structures that combines field monitoring, numerical simulations, codal provisions, and Chang's comfort chart. The method utilizes ambient vibration tests (AVT) and operational modal analysis (OMA) to create a reliable finite element (FE) model for the structure. It involves analyzing the time history and calculating the peak acceleration values at various points within the structure using synthetic ambient wind forces derived from superposing waves. The comfort assessment compares peak acceleration values estimated from time history analysis against those provided in Chang's chart for different comfort levels. The effectiveness of the proposed method is demonstrated through a case study on a tall, slender reinforced concrete (RC) staircase structure, confirming its suitability for practical applications.