Bed Pressure Research Articles

Functional textiles for prevention of pressure ulcers – a review

Purpose This paper aims to summarize researches conducted related to functional textiles for prevention of pressure ulcers and critical analysis of the outcomes to pave path for the future research in this area for benefit of the patients. Pressure ulcers, also known as bed sores, pressure sores and decubitus ulcers, are localized areas of tissue damage that develop due to pressure usually over a bony prominence. A standard hospital mattress has an interface pressure of 100 mmHg which can result in pressure ulcers unless repositioning occurs at regular intervals. Moisture accumulation on the skin is an important physical factor predisposing a patient to the occurrence of pressure ulcers and tissue breakdown. The disability leads to several requirements of functional clothing and textile products. The textiles play a variety of roles in this concern, from simply having good aesthetic appearance to preventing life threatening risks. An ideal support surface prevents pressure ulcers by providing pressure redistribution and maintaining a healthy skin microenvironment. The use of the textiles for the care of elderly disabled and bedridden persons can play an important role, as their quality of life can be improved by making use of functional and good-looking textiles. Design/methodology/approach This review paper aims to summarize researches conducted related to functional textiles for prevention of pressure ulcers and critical analysis of the outcomes to pave path for the future research in this area for benefit of the patients. Findings In the past years, there have been several functional textiles developed for the prevention of pressure ulcer. They are designed to maintain proper microclimate around patient skin. Sheepskin is one of the oldest used bed overlays which prevent pressure ulcer but its prolonged use leads to uneasy feeling for the patient. A sensor in bed for pressure detection is one of the good alternatives as it provides proper indication on when to change the position of the patient so that the pressure can be shifted and ulcers is prevented. These sensors are costly and complex to setup so for common man they are not easily available. Multilayer textiles on the other hand are complex to make as the properties are dependent upon the fiber content, yarn structure, fabric structure and technique of layering them together. Spacer fabric provides good air and moisture permeability, but there is a scope to study this type of fabric by varying the fibers type and thickness of the spacer fabric. A bedding material which is not much complex and can be easily purchased and used by common man for in-house usage is the need of the hour. Originality/value There is no comprehensive review available regarding research in this area with critical analysis of the outcomes for future study.

Particle segregation in spouted bed pyrolysis reactor: Sand-coconut shell and sand-cocoa shell mixtures

The singularity of air-particle flow characteristics and segregation phenomenon are still the main obstacles for application of conical spouted bed (CSB) for fast pyrolysis. This paper aims to investigate statistically the operating parameters (minimum spouting velocity and bed pressure drop) and biomass segregation (biomass mixing index) in a CSB composed of biomass (coconut and cocoa shells) and sand mixtures. Models for the pressure drop and inlet air velocity at the minimum spouting condition and for the axial mixing index were obtained. The bed voidage does not change significantly with the increase of biomass mass fraction (coconut and cocoa shells), therefore, larger amounts of biomass can be used without greatly increasing or decreasing the inlet air velocity to stabilize the spouted regime. From the analysis of bed stability and particle segregation, significant insights were obtained for future application of the CSB for the pyrolysis of biomasses. It is recommended the use of mixtures with 40 wt% of coconut shells and 75 wt% of cocoa shells in initial pyrolysis tests in CSB reactor. The cocoa shells particles are more suitable to pyrolysis because of their higher flowability.

Numerical Simulation of Hydrodynamics in a Turbulent Contact Absorber: A Simplified Approach

In the current work, hydrodynamics of a turbulent contact absorber (TCA) was studied in terms of bed pressure drop and expanded bed height by adopting a simplified modeling approach. The study was carried out computationally using the Eulerian multifluid model in ANSYS Fluent® where the packing was treated as a granular material. In order to simplify the complex three-phase system, it was reduced to a two-phase configuration by considering the solid packing and liquid water as a single phase with appropriate modifications. Both the laminar and turbulent viscous models were tested to study the bed characteristics at different values of liquid and gas flow rates. The covered range of liquid velocity was 0.004–0.012 m/s and that of gas velocity was 1.8–3.6 m/s. It was found that laminar model was able to produce better results as compared to turbulent one. The simulation results for pressure drop across the bed agreed well with the published experimental data. However, for a fixed gas velocity with variable liquid holdup, the bed expansion displayed a reverse trend as compared to experiments. Hence, the current model can be used to predict bed pressure drop of TCA-type systems, but not the expanded bed height.

Data analysis of a paste thickener

Abstract The solids content of slurry is typically increased in thickeners. A clean overflow and maximum solids concentration in the underflow are the general targets. The flocculant rate and underflow rate are the two independent variables that are typically used for control. The dependent variables include rake torque, underflow density, overflow turbidity, solids interface level (bed depth), solids inventory (bed pressure), solids settling rate and underflow viscosity. The research problem in question is that the outgoing paste is sometimes difficult to pump. The phenomena leading to this situation are not well known. In the worst-case scenario these phenomena cause clogging in the piping. A data analysis has been done to find the variables that affect and correlate with the pumping problem. The scope of this study covers the measurements from the feed line, thickener and underflow. The goal is to gain better understanding of the phenomena after this phase. The data analysis was done using the paste line pressure difference as a response variable and by dividing the data collected from Yara’s Siilinjärvi mill into two parts: operation areas with high and low pressure difference. The analysis is focused on Thickener 1 due to better availability of measurements. The knowledge of the variables found to influence the pressure difference can be utilized in further development.

Endovascular Therapy for Patients With Acute Ischemic Stroke During the COVID-19 Pandemic: A Proposed Algorithm.

Endovascular Therapy for Patients With Acute Ischemic Stroke During the COVID-19 Pandemic: A Proposed Algorithm.

Effect of particle properties on forces on an immersed horizontal slat during start-up of a fluidized bed

To study the effect of particle properties on forces acting on immersed internals during start-up of fluidized bed reactors, forces on a horizontal slat were measured in fluidized beds of four types of particulate materials (i.e. FCC catalyst particles and three silica sands of different sizes). The forces were measured by strain gauges adhered on the slat surface. Transient pressure signals were also measured synchronously by pressure transducers. The experimental results show that a high upward stress impulse appears in the measured stress signals during start-up of the fluidized beds of FCC particles and the two smaller-size silica sands. The peak stress impulse was several times larger than the magnitude of stress signals measured during steady state operation. However, in the fluidized bed of the coarsest silica sand, the peak stress impulse during start-up was much smaller, which is close to the magnitudes measured during steady state fluidization. For the three sizes of silica sands, the effective peak load densities on the slat decreased significantly with increasing particle size and were approximately proportional to the calculated fixed bed pressure drops of these beds based on Ergun equation. On the other hand, during start-up of the fluidized bed of FCC particles, particles near the bottom of the bed were difficult to mobilize and collapse, resulting in the bed expanding considerably and requiring more time to transform into a fluidized state. Potentially, internals immersed in the fluidized beds of small particles are easier to damage during the start-up stage. Effective measures (e.g. starting up the bed gradually with small increments of superficial gas velocity) must be implemented to reduce the possible risks for internals immersed in these fluidized beds.

P192 Crystallising care: improving hospital gout management

Abstract Background Gout is the most common cause of a hot swollen joint, and a major contributor to inpatient rheumatology workload. Recently published data demonstrated that hospital admissions due to gout increased by 59% in England from 2006 - 2017. The mean length of stay for a gout admission was 6 days in 2017; a figure that has not changed significantly over the last decade. We hypothesised that a key contributing factor to prolonged hospital stays in patients presenting with gout attacks is delayed joint aspiration and synovial fluid analysis. We investigated time to joint aspiration, and time taken to obtain a crystal analysis result, in acute rheumatology referrals at a large tertiary centre. Methods Electronic Health Records (EHR) system data were accessed for all joint aspirate crystal analyses in a 4-month window in 2017. EHR system documentation contains all clinical notes, electronic referrals, and laboratory requests with indicative coded timestamps. Pre- and post-aspirate differential diagnoses were compiled from the clinical record. Manual verification of the clinical records ascertained whether there was any delay in discharge pertaining to a crystal analysis. For representation, time figures were rounded to the nearest hour. Results Over a 4-month period, 38 patients who had been referred to the inpatient rheumatology team at King’s College Hospital had crystal analysis performed following joint aspiration; 24 from an emergency department setting, and 14 from an inpatient ward setting. The proportions of these cases by articular distribution (with the specific joint aspirated in brackets) were: 55% monoarthritis (knee), 16% oligoarthritis (knee), 16% polyarthritis (knee), 10% polyarthritis (wrist), 3% monoarthritis (elbow). Mean time from rheumatology referral to joint aspiration was 7 hours (range 1-21; median 5; IQR 3-8). The mean time from sample acquisition to crystal analysis result was 20 hours (range 1-95; median 16; IQR 4-21). Discharges for 17/38 (45%) patients were pending crystal analysis results, of which 10/17 (59%) patients were discharged without results. Rheumatology clinician pre-test diagnostic accuracy was 55%. Comparing pre-aspirate diagnosis with final diagnosis, proportionately septic arthritis was over-diagnosed, whilst gout was under-diagnosed. Conclusion Gout remains a difficult condition to promptly differentiate and treat in hospital. Clinician workload and joint aspiration burden are rising due to global incidence trends. A move to establish a “7-day NHS” and significant bed pressures have developed since the British Society for Rheumatology (BSR) hot swollen joint guideline was published. In our centre, inadequate crystal diagnostics appear to be driving prolonged length of stay. Further evaluation of causal factors in the delay of recognition, referral and diagnostics is required. Through application of quality improvement methodology, process-mapping and driver diagrams we plan to implement a point-of-care testing (POCT) and door-to-needle (DTN) programme, researching how to improve the gout patient’s experience. Disclosures B.D. Clarke None. M.D. Russell None. A.I. Rutherford None. J.B. Galloway None. J. Stack None.

Process Failure Detection via Recurrence Quantification Analysis in a Slot-Rectangular Spouted Bed

Abstract A study was conducted to explore the applicability of recurrence and recurrence quantification analysis (RQA) to the detection of process failures in spouted bed reactor systems. Three different potential failure modes were examined in a transparent, cold flow slot-rectangular spouted bed. These being, a simulated air leak from a side wall of the reactor, a simulated gas leak from the top wall of the reactor, and simulated agglomeration of solids via introduction of larger “klinker” particles. Bed pressure drop time history data were collected and analyzed via generation of recurrence plots (RPs) and RQA parameters. In general, the simulated agglomeration case was quite easily detected via ever RQA Parameter examined, whereas the simulated air leaks were detected by only a single RQA parameter.

Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

AbstractCatalytic fixed‐bed reactors with a low tube‐to‐particle diameter ratio are widely used in industrial applications. The heterogeneous packing morphology in this reactor type causes local flow phenomena that significantly affect the reactor performance. Particle‐resolved computational fluid dynamics has become a predictive numerical method to analyze the flow, temperature, and species field, as well as local reaction rates spatially and may, therefore, be used as a design tool to develop new improved catalyst shapes. Most validation studies which have been presented in the past were limited to simple particle shapes. More complex catalyst shapes are supposed to increase the reactor performance. A workflow for the simulation of fixed‐bed reactors filled with various industrially relevant complex particle shapes is presented and validated against experimental data in terms of bed voidage and pressure drop. Industrially relevant loading strategies are numerically replicated and their impact on particle orientation and bed voidage is investigated.

Study on ultra-low NOX emission technology of 660 MW ultra-supercritical circulating fluidized bed boiler

For the first 660MW ultra-supercritical circulating fluidized bed boiler in China, the original NOX emission concentration would be controlled and maintained below 50mg/Nm3, by improving the uniformity of bed temperature and bed pressure, strengthening the secondary air fractional combustion, optimizing the combustion temperature and operating oxygen and so on. Meanwhile, selective non-catalytic reduction (SNCR) technology with urea as reducing agent is selected as the auxiliary method to ensure the boiler achieves ultra-low NOX emission under full load conditions.

Research on selection optimization technology of air fan for ultra-supercritical circulating fluidized bed boiler

In recent years, with the improvement of the capacity and parameters of domestic CFB boiler units and the potential of technology from design, operation adjustment and equipment transformation, the CFB technology has been relatively mature, and economic indicators are significantly improved. The successful application of new technologies in project provides good conditions for the development of selection optimization technology of air fan. Combined with the application and project practice of the energy-saving technology of air fan for supercritical CFB boiler in service, the energy distribution of air fan after design and energy-saving transformation is quantitatively analyzed through the experiment. Based on this, the energy-saving technology of air fan is researched. From the low bed pressure design, selection optimization of air fan parameter and frequency conversion energy-saving, the selection optimization technology of air fan for ultra-supercritical CFB boiler is proposed, which provides a technical basis for the lower energy consumption technology of ultra-supercritical CFB boiler design in the future.

Performance enhancement of a biofilter with pH buffering and filter bed supporting material in removal of chlorobenzene

Acidic substances, which produced during chlorinated volatile organic compounds, will corrode the commonly used packing materials, and then affect the removal performance of biofiltration. In this study, three biofilters with different filter bed structure were established to treat gaseous chlorobenzene. CaCO3 and 3D matrix material was added in filter bed as pH buffering material and filter bed supporting material, respectively. A comprehensive investigation of removal performance, biomass accumulation, microbial community, filter bed height, voidage, pressure drops, and specific surface area of the three biofilters was compared. The biofilter with CaCO3 and 3D matrix material addition presented stable removal performance and microbial community, and greater biomass density (209.9 kg biomass/m3 filter bed) and growth rate (0.033 d−1) were obtained by using logistic equation. After 200 days operation, the height, voidage, pressure drop, specific surface area of the filter bed consisted of perlite was 27.4 cm, 0.39, 32.8 Pa/m, 974,89 m2/m3, while those of the filter bed with CaCO3 addition was 28.2 cm, 0.43, 21.3 Pa/m, and 1021.03 m2/m3, and those of the filter bed with CaCO3 and 3D matrix material addition was 28.7 cm, 0.55, 17.4 Pa/m, and 1041.60 m2/m3. All the results verified the biofilter with CaCO3 and 3D matrix material addition is capable of sustaining the long-term performance of biofilters. CaCO3 could limit the changes of removal efficiency, microbial community and filter bed structure by buffering the pH variation. And 3D matrix material could maintain the filter bed structure by supporting the filter bed, regardless of the buffering effect.

Characterization of Hyporheic Exchange Drivers and Patterns within a Low-Gradient, First-Order, River Confluence during Low and High Flow

Confluences are nodes in riverine networks characterized by complex three-dimensional changes in flow hydrodynamics and riverbed morphology, and are valued for important ecological functions. This physical complexity is often investigated within the water column or riverbed, while few studies have focused on hyporheic fluxes, which is the mixing of surface water and groundwater across the riverbed. This study aims to understand how hyporheic flux across the riverbed is organized by confluence physical drivers. Field investigations were carried out at a low gradient, headwater confluence between Baltimore Brook and Cold Brook in Marcellus, New York, USA. The study measured channel bathymetry, hydraulic permeability, and vertical temperature profiles, as indicators of the hyporheic exchange due to temperature gradients. Confluence geometry, hydrodynamics, and morphodynamics were found to significantly affect hyporheic exchange rate and patterns. Local scale bed morphology, such as the confluence scour hole and minor topographic irregularities, influenced the distribution of bed pressure head and the related patterns of downwelling/upwelling. Furthermore, classical back-to-back bend planform and the related secondary circulation probably affected hyporheic exchange patterns around the confluence shear layer. Finally, even variations in the hydrological conditions played a role on hyporheic fluxes modifying confluence planform, and, in turn, flow circulation patterns.

Backwashing behavior and hydrodynamic performances of granular activated carbon blends

Ozone-biological activated carbon (O3-BAC) process has been proved to be an efficient and cost-effective technology in advanced treatment of drinking water. However, O3-BAC raises strict requirements in adsorption, hydrodynamic and regeneration performances, which one single activated carbon could hardly all-sided meet. Blending activated carbons seems to be an appropriate and economically feasible method to deal with the issue. Thus, the uniformity and stability of activated carbon blends during water treatment, especially in backwashing process are of great importance. In this paper, cyclic experiments of downward adsorption and upward backwash on 11 typical commercial granular coal-based activated carbons and their blends were carried out in column test. Hydrodynamic performances such as bed expansion rate and bed pressure drop were measured. The uniformity and stability of activated carbon blends were investigated by determining iodine number of samples collected from different heights of activated carbon bed. Then, both traditional regression methods and back-propagation neural network model were utilized to predict superficial velocity at 30% bed expansion rate and maximum bed pressure drop of activated carbon blends. The results indicate that water backwashing process has no effect on the composition proportion of activated carbon blends, and slightly changes the particle distribution of activated carbon bed regarding pore structure and adsorption capacity. A three-layer back-propagation neural network model for superficial velocity at 30% bed expansion rate yields mean relative errors of 2.17%, which is much lower than that given by traditional regression methods such as 5.53% (weighted average), 4.08% (linear) and 4.06% (polynomial). Moreover, the back-propagation neural network model for maximum bed pressure drop yields mean relative errors of 1.37%, which is much lower than that given by traditional regression methods such as 4.31% (weighted average), 4.28% (linear) and 4.22% (polynomial). The non-linear relationships can be accurately identified by the back-propagation neural network model.

Machine learning–based optimization for hydrogen purification performance of layered bed pressure swing adsorption

An adsorption, heat and mass transfer model for the five-component gas from coal gas (H2/CO2/CH4/CO/N2 = 38/50/1/1/10 vol%) in a layered bed packed with activated carbon and zeolite was established by Aspen Adsorption software. Compared with published experimental results, the hydrogen purification performance by pressure swing adsorption (PSA) in a layered bed was numerically studied. The results show that there is a contradiction between the hydrogen purity and recovery, so the multi-objective optimization algorithms are needed to optimize the PSA process. Machine learning methods can be used for data analysis and prediction; the polynomial regression (PNR) and artificial neural network (ANN) were used to predict the purification performance of two-bed six-step process. Finally, two ANN models combined with sequence quadratic program (SQP) algorithm were used to achieve multi-objective optimization of hydrogen purification performance. According to the analysis of the optimization results, the ANN models are more suitable for optimizing the purification performance of hydrogen than the PNR model.

Can syndromic surveillance help forecast winter hospital bed pressures in England?

Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions. We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included. We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models. Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity.

An investigation on the heat transfer model for immersed horizontal tube bundles in a pressurized fluidized bed

In order to predict the heat transfer coefficient between the immersed horizontal tube bundles and the pressurized fluidized bed, different types of heat transfer models research process for the horizontal tube surface are presented. The accuracy of these models has been analyzed with the data of pressurized experiments, which indicates the limitation of these models in the application of pressurized fluidized bed. A new semi-empirical emulsion renewal model is proposed which takes the advantages of thermal contact resistance model and heat penetration model into account and modifies the correlation for gas convection heat transfer calculation at elevated pressure. The total experimentally reported 89 points from different sources with pressures ranging 0.1–1.6 MPa, particle diameter 240–700 μm are predicted within the absolute average deviation of 10.25%, which is much lower compared with other models for the same data. The satisfactory description for the influence rule of bed pressure, temperature, gas velocity and particle diameter on the heat transfer coefficient was also given from the model.

An Assessment of Point-of-Care PCR Testing for the Diagnosis and Management of Meningo-Encephalitis

BACKGROUND Meningitis and Encephalitis are potentially fatal infections. When suspected, empirical treatment is started, and only safely discontinued once excluded. The impact of current CSF investigations is prolonged inpatient stay, and exposure to broad-spectrum antimicrobials. Biofire Filmarray is a point-of-care PCR system. Our aim was to assess time to BioFire result, and its impact on clinical management. METHOD BioFire was implemented, in addition to current practice, on CSF samples with WCC ≥10 and all neonatal samples processed between November 2018 and February 2019. Data was collected prospectively for: patient demographics, sampling time, time to result of BioFire and current PCR, antimicrobial regime, and early discharge. Percentage agreement between BioFire and current PCR, mean time to result, percentage cases with reduction in antimicrobials, and mean length of stay for those discharged based on BioFire, were calculated. RESULTS There were 22 samples analysed. There was an 86.4% agreement between BioFire and current PCR. In cases of disagreement, BioFire identified pathogens where standard PCR had not. One sample was insufficient for virology PCR however, a full array was obtained from BioFire. Mean time to BioFire result authorization was 17.8 hours, compared to 316 for virology PCR and 331.2 for bacteriology PCR. BioFire allowed narrowing of antimicrobial therapy in 22.7% of patients, discontinuation in 41.0%, and early discharge in 27.3%. CONCLUSION BioFire provides comparable diagnosis of meningo-encephalitis faster than current practice. With the current focus on rising bed pressures and antimicrobial stewardship, BioFire allows targeted therapy and safe early discharge where infection is excluded.

Hydrodynamic Characterization of a Shallow Rectangular Spouted Bed Using Bed Pressure Signals and Image Processing Methods

To support the design of spouted bed reactors, experiments are performed in a rectangular spouted bed to measure the peak pressure drop (ΔPmax) and the internal and external spouting velocities (Uis and Ues). Four particle types spanning under Geldart D and B are used. Uis and Ues are measured from bed pressure drop and expansion ratio profiles, respectively, with the Ues/Uis ratio of each particle type obtained. Correlations predicting the ΔPmax of Geldart D and B particles are developed by reviewing published correlations and investigating the nozzle effect. Good prediction is achieved with a slope of 0.997 and an adjusted R2 of 0.998 in a 95% confidence interval. Ues is predicted through correlations developed by adding effects of dp/Di and H0 in the Mathur–Gishler equation. The calculated Ues agrees well with the experimental data, achieving a slope of 0.998 and an adjusted R2 of 0.998 in a 95% confidence interval.

Optimization of Fluidization State of a Circulating Fluidized Bed Boiler for Economical Operation

To reduce the auxiliary power consumption and improve the reliability of large-scale circulating fluidized bed (CFB) boilers, we developed energy-saving CFB combustion technology based on the fluidization state re-specification. A calculation model of coal comminution energy consumption was used to analyze the change in comminution energy consumption, and a 1D CFB combustion model was modified to predict the operation parameters under the fluidization state optimization conditions. With a CFB boiler of 480 t/h, the effect of fluidization state optimization on the economical operation was analyzed using the above two models. We found that combustion efficiency presents a nonmonotonic trend with the change in the bed pressure drop and feeding coal size. There are an optimal bed pressure drop and a corresponding feeding coal size distribution, under which the net coal consumption is the lowest. Low bed pressure drop operation achieved by reducing the coal particle size is not beneficial to SO2 and NOx emission control, and the pollutant control cost increases. The effect of fluidization state optimization on the gross cost of power supply can be calculated, and the optimal bed pressure drop can be obtained.