Scale-down Model Research Articles

Augmenting the seismic performance of masonry models using polypropylene band and steel wire mesh through shaking table testing

The seismic vulnerability of unreinforced masonry (URM) structures was observed during the past seismic events, which caused a huge loss of life and property. However, URM buildings are quite common in developing countries like India as they offer cheap shelters to people with low income. An easily implementable strengthening technique with cost-effective materials for enhancement of the seismic behaviour of URM building is of utmost importance. Hence, this study was carried out to develop a technique to improve the strength and ductility of URM buildings. Clay bricks and eco-friendly fly-ash bricks were used for the construction of the building models. Brick sizes were reduced to half so that the scale-down building model can be constructed for testing. The building models were tested in a uni-directional shaking table using swept sine motions. The experimental investigation was categorized in three phases. In the first phase, the effect of diaphragm action on seismic behaviour of masonry building was investigated by providing the flat reinforced concrete slab and pitched timber truss as a roof on top of the building. The second phase focused on the enhancement of the seismic behaviour of the URM wall by strengthening with two cost-effective materials, such as polypropylene (PP) band and steel wire mesh (WM). In the third phase, cracked (damaged) URM walls were repaired and retrofitted with wire mesh. It was observed that both the strengthening materials were effective in improving the ductility of the URM buildings.

Identification of the running status of membrane walls in an opposed fired model boiler under varying heating loads

To understand the running status of membrane walls in an opposite firing boiler, a scale-down model furnace was established, and the temperature, heat flux, strain and stress distributions are investigated under four heating loads. Results show that the average membrane wall temperature and heat flux present a continuous increase from 42 °C and 16 W/m2 to 96 °C and 50 W/m2, respectively, with the heating load increase from 25% to full load. The average strain and stress also rise from 88.7 µm and 0.094 MPa to 152.5 µm and 0.148 MPa when the heating load increases from 25% to 50%, but then they keep stable when further increasing the heating load. General distribution patterns of each tested parameter are found relatively similar under varying heating loads. High strain and stress distributions are always detected at the middle left zone of side walls and the middle of the rear wall, where wall temperatures are measured high. External fixed constraints and high-temperature thermal strain is found jointly affecting the strain and stress distribution of the membrane wall. A simplified mechanism of how the strain and stress on boiler membrane walls evolve is proposed after comprehensive discussion of the measurement results.

A New Perspective on Scale-Down Strategies for Freezing of Biopharmaceutics by Means of Computational Fluid Dynamics

Common approaches to scale-down freeze-thaw systems are based on matching time-temperature profiles at corresponding points; however, little is known about the differences in anisotropy between the 2 scales. In this work, computational fluid dynamics modeling was used to investigate these differences. The modeling of the convective flow of the liquid phase within ice porous structure and volume expansion caused by freezing enabled accurate prediction of the local temperature and composition, for evaluation of potential stresses on protein stability, such as cryoconcentration and time in the nonideal environment. Overall, the small height of the scale-down containers enhances cryoconcentration. The time under stress was consistent in both scales, except when the walls of the container could deform. In general, the common approach of matching the time-temperature profile at the center of the containers was more effective as a worst-case scenario than a scale-down model. This work shows that instead of considering a single matching time-temperature location; one should aim for a more general perspective by measuring many locations. Container geometries and heat transfer rates should be designed to match stresses related to protein integrity for equivalent mass fractions between both scales, which can be achieved with the assistance of computational fluid dynamics models.

Rapid process development of serum-free pseudorabies virus production with the Quality by Design approach.

This study described a successful application of the Quality by Design (QbD) approach to pseudorabies virus (PRV) production process development in a fixed-bed bioreactor using the serum-free medium (SFM). The innovated tube-fixed-bed bioreactor was used as a scale-down model of the fixed-bed bioreactor for process development. Risk analysis was performed using Ishikawa diagram combined with failure mode effects analysis (FMEA). The comparative experiment was performed to screen proper medium for adherent African green monkey kidney (Vero) cells from three commercially available SFMs (VP-SFM, ProVERO-1 and Vero-A). The Vero-A medium showed as an outstanding one for further study. The PRV titer in harvest medium was consider as Critical Quality Attribute (CQA) and the Critical Process Parameters (CPPs) [time of infection (TOI), multiplicity of infection (MOI) and initial inoculation cell density] ranked high with risk priority number (RPN) were taken into design of experiment (DoE) methodology. Then prediction model of PRV production process was established and a robust PRV production process was explored. Under the robust setpoint conditions, the Xcell 1L laboratory-scale fixed-bed bioreactor yielded PRV titer up to 7.87 log10 TCID50/mL at 3dpi, which was comparable with that in the tube-fixed-bed bioreactor. Combination of the tube-fixed-bed bioreactor and QbD approach could further accelerate the development of a robust virus production process.

Applying Deep Learning to Continuous Bridge Deflection Detected by Fiber Optic Gyroscope for Damage Detection.

Improving the accuracy and efficiency of bridge structure damage detection is one of the main challenges in engineering practice. This paper aims to address this issue by monitoring the continuous bridge deflection based on the fiber optic gyroscope and applying the deep-learning algorithm to perform structural damage detection. With a scale-down bridge model, three types of damage scenarios and an intact benchmark were simulated. A supervised learning model based on the deep convolutional neural networks was proposed. After the training process under ten-fold cross-validation, the model accuracy can reach 96.9% and significantly outperform that of other four traditional machine learning methods (random forest, support vector machine, k-nearest neighbor, and decision tree) used for comparison. Further, the proposed model illustrated its decent ability in distinguishing damage from structurally symmetrical locations.

Optimal Power Flow Control in Parallel Operating AC and DC Distribution Links

DC links with back to back voltage source converters are usually built alongside the existing medium voltage ac distribution grids for infrastructure reinforcement. The distribution network operators need to run multiple of such parallel ac and dc links between two substations at optimal efficiency. This article shows that the active power steering capability of the dc link can be used to dynamically vary the share of power flow in the ac link such that the system operating efficiency is maximized for varying power demand, grid voltage, dc-link voltage, converter efficiency, link length, and conductor area. The algorithm developed based on the derived exact and estimated solution for this parallel ac-dc link power sharing ratio is proved through simulations on a 10 kV, 30 MVA system. The concept is validated using experiments on a scale-down lab model. Using case-study with adapted measured substation data of hourly average power demand profile for one year, it is shown that annual energy saving potential in the range of 8-92 MWh can be achieved with varying link length between 10-20 km for 5-20 kV grid voltage and 185-630 mm$^2$ conductor area if the proposed optimal power flow control is used.

Scale-Down Models to Support Process Characterization

Scale-Down Models to Support Process Characterization

Experimental and numerical investigation on the detailed buckling process of similar stiffened panels subjected to in-plane compressive load

Abstract There are two aims in the present paper. The first one is to see and understand the detailed buckling process, especially the interactions between material nonlinearity and geometric nonlinearity on the post-buckling stage, of stiffened panels subjected to in-plane compressive load. The second one is to validate the similarity criteria of designing different sizes of stiffened panels which have the same buckling modes and proportional ultimate strength. These similar relationships make it possible to predict the buckling behavior and ultimate strength of a full-size structure by testing its scale-down model. To these ends, three different sizes of stiffened panels with the same flexural rigidity ratio, plate slenderness and column slenderness, were designed, manufactured and tested. In order to trace and analysis the detailed buckling process, three-dimensional digital image correlation (3D-DIC) method was employed. So, the integrated evolution process of global deformation and strain distribution fields of the stiffened panels were obtained. These data also provide accurate data to verify the numerical or theoretical method in predicting the bulking, especially post-buckling process and ultimate strength of stiffened panel. Results show that the three stiffened panels have reasonable similarity relationships of the buckling failure process. Finally, finite element models with measured initial imperfections were established to reappear the experimental process. The numerical results agree well with the experimental data.

Design of A scale-down experimental model for SFR reactor vault cooling system performance analyses

We propose a scaled-down experimental model of vertical air-natural convection channels by applying the modified Ishii–Kataoka scaling method with the assistance of numerical analyses to the Reactor Vault Cooling System (RVCS) of the Proto-type Gen-IV Sodium-cooled fast reactor (PGSFR) being developed in Korea. Two major non-dimensional numbers (modified Richardson and Friction number) from the momentum equation and Stanton number from the energy balance equation were identified to design the scaled-down experimental model to assimilate thermal-hydraulic behaviors of the natural convective air-cooling channel of RVCS. The ratios of the design parameters in the PGSFR RVCS between the prototype and the scaled-down model were determined by setting Richardson and Stanton number to be unity. The friction number which cannot be determined by the Ishii-Kataoka method was estimated by numerical analyses using the MARS-KS system code. The numerical analyses showed that the friction number with the form loss coefficient of 2.0 in the scale-down model would result in an acceptable prediction of the thermal-hydraulic behavior in RVCS. We also performed experimental benchmarking using the scaled-down model with the MARS-KS simulations to verify the appropriateness of the scale-down model, which demonstrated that the temperature rises and the average air flow velocity measured in the scale-down model.

Screening of Media Supplements for High-Performance Perfusion Cultures by Design of Experiment.

Perfusion is considered as the preferable unit operation mode for fully integrated continuous bioprocessing. However, the inherent complex process control, long process development times, and lack of suitable scale-down models for high-throughput screening are reasons why perfusion processes are still not routinely applied in cell culture technology. Advantages of perfusion are maintenance of a consistent cellular environment, a constant high-quality product flow, enhanced volumetric bioreactor productivity, and small lab footprint. Here, we provide guidelines for screening different proprietary but commercially available HyClone™ Cell Boost™ supplements in a Design of Experiment (DoE) approach to spike the HyClone™ CDM4NS0 basal media for enhanced product titers in small-scale TubeSpin models. These surrogate semi-perfusion cultures were successfully realized by a daily complete media exchange routine resulting in high viable cell densities for extended time periods at minimal media consumption. This technique was leveraged to define the potential of different perfusion media formulations.

Multivariate Data Analysis Methodology to Solve Data Challenges Related to Scale-Up Model Validation and Missing Data on a Micro-Bioreactor System.

Multivariate data analysis (MVDA) is a highly valuable and significantly underutilized resource in biomanufacturing. It offers the opportunity to enhance understanding and leverage useful information from complex high-dimensional data sets, recorded throughout all stages of therapeutic drug manufacture. To help standardize the application and promote this resource within the biopharmaceutical industry, this paper outlines a novel MVDA methodology describing the necessary steps for efficient and effective data analysis. The MVDA methodology is followed to solve two case studies: a "small data" and a "big data" challenge. In the "small data" example, a large-scale data set is compared to data from a scale-down model. This methodology enables a new quantitative metric for equivalence to be established by combining a two one-sided test with principal component analysis. In the "big data" example, this methodology enables accurate predictions of critical missing data essential to a cloning study performed in the ambr15 system. These predictions are generated by exploiting the underlying relationship between the off-line missing values and the on-line measurements through the generation of a partial least squares model. In summary, the proposed MVDA methodology highlights the importance of data pre-processing, restructuring, and visualization during data analytics to solve complex biopharmaceutical challenges.

Design and Characteristics Analysis of Coaxial Magnetic Gear for Contra-Rotating Propeller in Yacht

In this article, the design and characteristic research of the coaxial magnetic gear for the contra-rotating propeller in the premium yacht are presented. The scale-down model of 1/25 is reviewed as the research of the applicability of the coaxial magnetic gear. The space harmonic characteristics of the magnetic field in the coaxial magnetic gear with the low gear ratio from 1 to 2 are investigated, and the optimized models with the surface-mounted permanent magnet and quasi-Halbach array are obtained using the response surface method. In the several operating points of the diesel engine, the magnetic loss and the resultant thermal characteristics are analyzed and compared in each model. Finally, the desired coaxial magnetic for the contra-rotating propeller in the premium yacht is achieved.

Process characterization strategy for a precipitation step for host cell protein reduction.

Process characterization using QbD approaches has rarely been described for precipitation steps used for impurity removal in biopharmaceutical processes. We propose a two‐step approach for process characterization in which the first step focuses on product quality and the second focuses on process performance. This approach provides an efficient, streamlined strategy for the characterization of precipitation steps under the Quality by Design paradigm. This strategy is demonstrated by a case study for the characterization of a precipitation using sodium caprylate to reduce host cell proteins (HCP) during a monoclonal antibody purification process. Process parameters were methodically selected through a risk assessment based on prior development data and scientific knowledge described in the literature. The characterization studies used two multivariate blocks to decouple and distinguish the impact of product quality (e.g., measured HCP of the recovered product from the precipitation) and process performance (e.g., step yield). Robustness of the precipitation step was further demonstrated through linkage studies across the overall purification process. HCP levels could be robustly reduced to ≤100 ppm in the drug substance when the precipitation step operated within an operation space of ≤1% (m/v) sodium caprylate, pH 5.0–6.0, and filter flux ≤300 L/m2‐hr for a load HCP concentration up to 19,000 ppm. This two‐step approach for characterization of precipitation steps has several advantages, including tailoring of the experimental design and scale‐down model to the intended purpose for each step, use of a manageable number of experiments without compromising scientific understanding, and limited time and material consumption.

Production Process Development of Pseudorabies Virus Vaccine by Using a Novel Scale-Down Model of a Fixed-Bed Bioreactor

In this study, a novel tube-fixed-bed bioreactor which consists of a TubeSpin bioreactor 50 tube and 0.44 g macrocarriers was developed as the scale-down model of a fixed-bed bioreactor. The adherent Vero cell–based pseudorabies virus (PRV) production process was tested in this novel model. The Vero cells grew well in the tube-fixed-bed bioreactor, and the cell density reached 5.8 × 106 cells/mL after 7 days of culture. The PRV production parameters (time of infection, multiplicity of infection, and harvest process) were optimized in the tube-fixed-bed bioreactor. Then the optimized process (time of infection = 3 days, multiplicity of infection = 0.001 and multiple harvest process) was scaled up 25-fold to an Xcell 1-L laboratory-scale fixed-bed bioreactor and 125-fold to an Xcell 5-L fixed-bed bioreactor successfully. The total PRV harvest in the Xcell 1-L bioreactor at 5 days after infection (dpi) was 10.25 log10 TCID50 which corresponds to 177,827 doses of vaccine. The total PRV harvest in the Xcell 5-L bioreactor at 5 dpi was 11.13 log10 TCID50 which corresponded to 1,348,962 doses of vaccine. The comparable growth curve, metabolism, and PRV production profile of the scaled-up bioreactors confirmed the feasibility and scalability of the tube-fixed-bed bioreactor as a scale-down model of the fixed-bed bioreactor for virus production process development.

Turbulence Characteristics before and after Scour Upstream of a Scaled-Down Bridge Pier Model

Bridge pier scour is one of the main causes of bridge failure and a major factor that contributes to the total construction and maintenance costs of bridge. Recently, because of unexpected high water during extreme hydrologic events, the resilience and security of hydraulic infrastructure with respect to the scour protection measure along a river reach has become a more immediate topic for river engineering society. Although numerous studies have been conducted to suggest pier scour estimation formulas, understanding of turbulence characteristics which is dominant driver of sediment transport around a pier foundation is still questionable. Thus, to understand near bed turbulence characteristics and resulting sediment transport around a pier, hydraulic laboratory experiments were conducted in a prismatic rectangular flume using scale-down bridge pier models. Three-dimensional velocities and turbulent intensities before and after scour were measured with Acoustic Doppler Velocimeter (ADV), and the results were compared/analyzed using the best available tools and current knowledge gained from recent studies. The results show that the mean flow variable is not enough to explain complex turbulent flow field around the pier leading to the maximum scour because of unsteady flows. Furthermore, results of quadrant analysis of velocity measurements just upstream of the pier in the horseshoe vortex region show significant differences before and after scour.

A scale-down model of 4000-L cell culture process for inactivated foot-and-mouth disease vaccine production

The anticipated increasing demand for inactivated foot-and-mouth (FMD) disease vaccine calls for its larger production capacity, while development of a large-scale process typically requires high running cost and has very limited experimental throughput at manufacturing scale. Thus, an economic scale-down model of representing a large-scale process becomes necessary and essential. In this study, we used a systematic approach to establish a scale-down model representing a 4000-L culture process for FMD vaccine production by suspension BHK-21 cells. In detail, we firstly compared hydrodynamic properties of three bioreactors (14-L, 800-L and 4000-L) under three different conditions (equivalent mixing time, equivalent shear stress and equivalent volumetric power). We figured out equivalent volumetric power (P/V) potentially as an appropriate scale-down strategy, since it resulted in comparable calculated hydrodynamic parameters among three bioreactors. Next, we used computational fluid dynamics (CFD) simulation to provide more details about hydrodynamic environments inside the bioreactors, which supports the reliability of this scale-down strategy. Finally, we compared cell growth, metabolites, vaccine productivity and product quality attributes during FMD vaccine production by BHK-21 cells and observed very close performances among three bioreactors, which once again demonstrates the robustness of this scale-down model. This scale-down strategy can be applied to study variations and critical quality attributes (CQAs) in the resultant production process based on quality by design (QbD) principles, aiming at further more efficient optimization of vaccine production.

Development of numerical heat and mass transfer model for predicting total heat exchange performance in Energy Recovery Ventilator

An energy recovery ventilator (ERV) is a widely used equipment that can recover sensible and latent heat. To improve its performance, it is essential to understand the heat and moisture transfer mechanism in the ERV. Against this background, overarching objectives of this study are to develop mathematical/numerical models for predicting and clarifying the hygro-thermal (i.e. heat and moisture) transfer mechanism in the heat exchange element of the ERV in terms of (i) simplified model for sensitivity analysis, and (ii) comprehensive model to integrate hygro-thermal transfer equations with computational fluid dynamics (CFD) analysis. Toward this end, we conducted fundamental experiments to measure temperature, humidity, and enthalpy exchange efficiencies in the scale-down ERV unit model, and then, numerical analyses were conducted according to the experimental scenario. As results of this study, we confirmed the reasonable prediction accuracy of our proposed numerical models for predicting total heat exchange performances.

Systematic evaluation of high-throughput scale-down models for single-use bioreactors (SUB) using volumetric gas flow rate as the criterion

Developing representative bioreactor scale-down models is a critical part in process development and characterization. Here we present a systematic analysis of high-throughput scale-down models (ambr®250, 250 mL) developed for 500 L or 2000 L single-use bioreactors using engineering approaches. A main scaling criterion, vvm (volume of gas per volume of liquid per minute), was studied for scale-down model development after analyzing bioreactor hydrodynamic environment and gas transfer characteristics. Two different processes with distinguished peak cell densities (12–14 vs. 20–25 × 106 cells/mL) for a monoclonal antibody (mAb) were evaluated. We demonstrated that scaling-down using similar vvm as the criterion is feasible in reproducing large-scale gas transfer characteristics for both cell densities, though more challenging in high-density conditions. Furthermore, a range of pCO2 levels could be generated through vvm modulations. The same vvm approach was successfully applied to two other mAbs. Practical aspects of ambr®250 operations, especially the impact of background air sparge rate and antifoam addition on dissolved oxygen control and gas transfer, were also discussed. Understanding and managing gas transfer gaps between small- and large-scale bioreactors is expected to streamline scale-up effort, and equally importantly scale-down activities for process characterization.

Scale-down model qualification of ambr® 250 high-throughput mini-bioreactor system for two commercial-scale mAb processes.

Recent advances in high-throughput (HTP) automated mini-bioreactor systems have significantly improved development timelines for early-stage biologic programs. Automated platforms such as the ambr® 250 have demonstrated the ability, using appropriate scale-down approaches, to provide reliable estimates of process performance and product quality from bench to pilot scale, but data sets comparing to large-scale commercial processes (>10,000 L) are limited. As development moves toward late stages, specifically process characterization (PC), a qualified scale-down model (SDM) of the commercial process is a regulatory requirement as part of Biologics License Application (BLA)-enabling activities. This work demonstrates the qualification of the ambr® 250 as a representative SDM for two monoclonal antibody (mAb) commercial processes at scales >10,000 L. Representative process performance and product quality associated with each mAb were achieved using appropriate scale-down approaches, and special attention was paid to pCO2 to ensure consistent performance and product quality. Principal component analysis (PCA) and univariate equivalence testing were utilized in the qualification of the SDM, along with a statistical evaluation of process performance and product-quality attributes for comparability. The ambr® 250 can predict these two commercial-scale processes (at center-point condition) for cell-culture performance and product quality. The time savings and resource advantages to performing PC studies in a small-scale HTP system improves the potential for the biopharmaceutical industry to get products to patients more quickly.

Development and Qualification of a Scale-Down Mammalian Cell Culture Model and Application in Design Space Development by Definitive Screening Design.

Scale-down models are indispensable and crucial tools for process understanding and continuous process improvement in product life-cycle management. In this study, a scale-down model representing commercial-scale cell culture process of adalimumab biosimilar HS016 was first developed based on constant power per volume (P/V) principle and then qualified by multivariate data analysis (MVDA) and equivalence test method. The trajectories of the bench-scale process lie in the middle of the control range of large-scale process, built by multivariate evolution model based on nutrients, metabolites, and process performance datasets. This indicates that the small-scale process performance is comparable with that of the full-scale process. The final product titer, integrated viable cell density (iVCD), viability, aggregates, acid peak content, total afucosylation level, and high mannose content recognized as key process attributes (KPAs) or critical quality attributes (CQAs) were equivalent across the scales upon comparison using equivalence test method. The qualified scale-down model was then used for process characterization using a definitive screening design (DSD) where five independent variables including pH, shifted temperature, inoculation seeding density, viable cell density (VCD) at first feeding, VCD at temperature shift were evaluated. Three quadratic polynomial models for final product titer, aggregation, and high mannose were then established using the DSD results. The design space was finally developed using a probability-based Monte Carlo simulation method and was verified with the operation setpoint and worst-case condition. The case study presented in this report shows a feasible roadmap for cell culture process characterization.