Attainable Region Research Articles

In-situ wet milling for particle size control in continuous crystallization: Expanding the attainable region

Continuous mixed-suspension mixed-product removal crystallizer cascades are robust and proven options for continuous manufacturing. However, when applied to a late-stage drug substance the desired particle size could not be achieved due to rapid crystal growth and slow secondary nucleation kinetics. This necessitated a batch terminal milling operation to achieve particle size control (Johnson et al., 2021). To overcome this and to intensify the process, an in-situ high-shear wet mill was integrated into the continuous equipment train to achieve the target physical properties of the drug substance that met the quality and manufacturability criteria needed for the drug product. This article describes the workflow used to optimize the equipment set and operational parameters. Incorporation of a high-shear wet mill operated intermittently in the continuous drug substance process greatly expanded the attainable particle size region, improved product quality, reduced cycle time, and simplified process development and scale-up compared to the process of batch milling after continuous crystallization. Small scale batch milling experiments were used to characterize milling performance at lab and production scales and inform operational space. Several lab-scale continuous runs were then used to define the process operating space and validate the process parameters necessary to meet the particle specifications of the product. Scale-up of the equipment set for in-situ milling was also demonstrated. This approach was tested at lab-scale on representative material operating for 70 h while changing the particle size of the product in real time. This illustrated the potential of intermittent milling for model-free particle size control.

Evaluation of Ammonia Co-fuelling in Modern Four Stroke Engines

Ammonia is emerging as a promising alternative fuel for longer range decarbonised heavy transport, particularly in the marine sector due to highly favourable characteristics as an effective hydrogen carrier. This is despite generally unfavourable combustion and toxicity attributes, restricting end use to applications where robust health and safety protocols can be upheld. In the currently reported work, a spark ignited thermodynamic single cylinder research engine equipped with gasoline direct injection was upgraded to include gaseous ammonia port injection fuelling, with the aim of understanding maximum viable ammonia substitution ratios across the speed load operating map. The work was conducted under overall stoichiometric conditions with the spark timing re-optimised for maximum brake torque at all stable logged sites. The experiments included industry standard measurements of combustion, performance and engine-out emissions (including ammonia ‘slip’). With a geometric compression ratio of 12.4:1, it was possible to run the engine on pure ammonia at low engine speeds (1000–1800 rpm) at low to moderate engine loads in a fully warmed up state. When progressively dropping down below a threshold load limit, an increasing amount of gasoline co-firing was required to avoid engine misfire. Due to the favourable antiknock characteristics, pure ammonia operation was up to 5% more efficient than pure gasoline operation under stable operating regions. A maximum net indicated thermal efficiency (ITE) of 40% was achieved, with efficiency tending to increase with speed and load. For the co-fuelling of gasoline and ammonia in a pure ammonia attainable operating region, it was found that addition of gasoline improved the combustion, but these improvements were not sufficient to translate into improved thermal efficiency. Emissions of ammonia slip reduced with increased gasoline co-fuelling, albeit with increased NOx. However, the reduction in ammonia slip was nearly ten times the increase in NOx emissions. Comparing pure ammonia and pure gasoline operation, NOx reduced by ~60% when switching from pure gasoline to pure ammonia (as the latter is associated with longer and cooler combustion). Results were finally compared to those obtained a modern multicylinder Volvo ‘D8’ turbo-diesel engine modified for dual-fuel operation with ammonia port fuel injection (PFI), with the focus of the comparison being ammonia slip and NOx emissions.

Extending the lower bound of attainable load-independent voltage gain values range in contactless, feedbackless and sensorless power delivery links

It is well-known that series(capacitive)-series(capacitive) compensated inductive wireless power transfer links (SS(CC)-IWPTL) operating at fixed frequency with constant coupling coefficient may be designed to attain arbitrary load independent voltage gain (LIVG) value, residing within a region defined only by loosely coupled transformer (LCT) parameters. Such a characteristic allows designing the system to be sensorless and operate without feedback, which is an extremely useful feature in hostile environment applications. Unfortunately, LCT parameters are not selected arbitrarily in practice; hence, the desired LIVG value may reside outside the attainable region, calling for an additional power conversion stage. In particular, region of attainable LIVG values is especially narrow when LCT inductances ratio is imposed by the application and thus cannot be freely selected. One of existing challenges is regulating the system output to low DC voltage while it is being fed from a much higher valued voltage source, i.e. calling for an extremely low LIVG value. The paper demonstrates that adopting an inductor rather than a capacitor as primary series compensation element allows to extend the lower bound of attainable LIVG values region for given LCT and operating frequency, potentially eliminating the need for an additional step-down power converter. Resulting coil-to-coil efficiency is quantified and guidelines for sizing corresponding compensation elements pair are established as well. Simulations and experiments accurately verify the proposed methodology.

Accounting for costs in attainable‐region‐based reactor–separation network synthesis: Models, tradeoffs, and insights

AbstractIn reaction engineering, the attainable region defines the set of all possible states attainable in the outlet stream of any steady‐state reactor network, given specified feed and reaction kinetics. Costs in approaches that aim to determine the attainable region are often neglected, resulting in targets that require expensive processes. In this work, we propose modeling methods that allow us to account for costs in reactor–separation synthesis while accurately identifying the attainable region. Our goal is to holistically analyze cost trade‐offs within the attainable region as well as provide a method to obtain practical targets to be used as benchmarks. We generate the attainable region using the continuous stirred tank reactor (CSTR) equivalence principle and introduce separation models accounting for costs to perform the required separation tasks. Through several case studies, we show how some subregions, typically close to the attainable region boundary, are expensive to achieve.

Optimal Pathways for Nitric Acid Synthesis Using P-Graph Attainable Region Technique (PART)

Developing a chemical reaction network is considered the first and most crucial step of process synthesis. Many methods have been employed for process synthesis, such as the attainable region (AR) theory. AR states that a region of all possible configurations can be defined with all the potential products and reactants. The second method is process network synthesis (PNS), a technique used to optimise a flowsheet based on the feasible materials and energy flow. P-graph is an algorithmic framework for PNS problems. P-graph attainable region technique (PART) is introduced here as an integration of both AR and P-graph to generate optimal reaction pathways for a given process. A descriptive AR plot is also developed to represent all the possible solution structures or reaction pathways. A case study of a conventional nitric acid synthesis process was used to demonstrate this technique.

Optimal reaction pathways of carbon dioxide hydrogenation using P-graph attainable region technique (PART)

The attainable region interpretation of the thermodynamic principles has indicated that carbon dioxide (CO2) can be either hydrogenated directly to form dimethyl ether (DME) or gasoline. The process that converts CO2 to DME is more thermodynamically favourable at lower temperature. A certain thermodynamic temperature range (25 to 300 °C) is suggested for the conversion of CO2 to DME via a methanol intermediate pathway without addition of work. Optimal synthesis routes derived from P-graph's mutual exclusion solver were compared with reactions reported in literature and showed great correlation. The reactions collectively possess Gibbs free energy of less than zero, and negative enthalpy of reaction. With P-graph attainable region technique, the case studies have demonstrated that the synthesis of DME and gasoline using CO2 hydrogenation via methanol intermediate and carbon monoxide intermediate from Fischer–Tropsch synthesis is feasible with no work and heat requirement. Both case studies have demonstrated visual advantage of P-graph and data-driven applications. The benefit of integrating the P-graph framework with machine learning model like decision tree classifier was also demonstrated in the second case study as it solves topological optimisation problems without scaling constraints.

Disability-Adjusted Life Expectancy and Cognitive Function among Community-Dwelling Adults.

We aimed to calculate disability-adjusted life expectancy (DALE) for Korean older adults based on their sex, educational attainment, and residential region across their cognitive status. We included 3,854 participants (aged 65-91years) from the Korean Longitudinal Study of Aging's seventh survey data. The participant's cognitive function status (normal, moderately impaired, or severely impaired) was determined based on cognitive examination and physical function independence, which was used to calculate their DALE. Females with normal cognition had higher DALE (7.60years, Standard Deviation (SD) = 3.88) than males (6.76, SD = 3.40); however, both sexes had comparable DALE for cognitive impairment. In contrast, the DALE values increased with higher educational achievements. Regarding residential areas, the DALE value for participants with normal cognition and moderate impairment was the highest among urban dwellers, while DALE for participants with severely impaired cognitive function was highest among rural dwellers; however, there were no statistically significant differences based on residential conditions. Our findings suggest that demographic characteristics should be considered when developing health policies and treatment strategies to meet the needs of the aging population in Korea.

Rational Continuous Neural Network Identifier for Singular Perturbed Systems With Uncertain Dynamical Models.

This study aims at designing a robust nonparametric identifier for a class of singular perturbed systems (SPSs) with uncertain mathematical models. The identifier structure uses a novel identifier based on a differential neural network (DNN) with rational form, which can take into account the multirate nature of SPS. The identifier uses a mixed learning law including a rational formulation of neural networks which is useful to solve the identification of the fast dynamics in the SPS dynamics. The rational form of the design is proposed in such a way that no-singularities (denominator part of the rational form never touches the origin) are allowed in the identifier dynamics. A proposed control Lyapunov function and a nonlinear parameter identification methodology yield to design the learning laws for the class of novel rational DNN which appears as the main contribution of this study. A complementary matrix inequality-based optimization method allows to get the smallest attainable convergence invariant region. A detailed implementation methodology is also given in the study with the aim of clarifying how the proposed identifier can be used in diverse SPSs. A numerical example considering the dynamics of the enzymatic-substrate-inhibitor system with uncertain dynamics is showing how to apply the DNN identifier using the multirate nature of the proposed DNN identifier for SPSs. The proposed identifier is compared to a classical identifier which is not taking into account the multirate nature of SPS. The benefits of using the rational form for the identifier are highlighted in the numerical performance comparison based on the mean square error (MSE). This example justifies the ability of the suggested identifier to reconstruct both the fast and slow dynamics of the SPS.

Integration of reactor network synthesis: A literature review and opportunities for future research

AbstractThe reactor network synthesis (RNS) is one of the subtopics of the chemical process synthesis, the purpose of which is to find an optimal reactor network for the specific objective function of the studied reaction system. This review discusses the principles, advantages, and disadvantages of various methods of RNS, together with the state of the research in each field. These methods could be divided into four categories: the process‐based approach (such as the attainable region, the targeting approach, and the method based on the elementary process functions), superstructure‐based approach, stochastic optimization, and parametric method. Finally, the paper discusses the existing problems of RNS in academic researches and practical applications, as well as its research directions in the future. This paper is helpful to the readers who have interests in the design and optimization of the reactor networks.

Multilevel Calibration Weighting for Survey Data

AbstractIn the November 2016 U.S. presidential election, many state-level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading explanation for this polling miss is that the precipitous decline in traditional polling response rates led to greater reliance on statistical methods to adjust for the corresponding bias—and that these methods failed to adjust for important interactions between key variables like educational attainment, race, and geographic region. Finding calibration weights that account for important interactions remains challenging with traditional survey methods: raking typically balances the margins alone, while post-stratification, which exactly balances all interactions, is only feasible for a small number of variables. In this paper, we propose multilevel calibration weighting, which enforces tight balance constraints for marginal balance and looser constraints for higher-order interactions. This incorporates some of the benefits of post-stratification while retaining the guarantees of raking. We then correct for the bias due to the relaxed constraints via a flexible outcome model; we call this approach “double regression with post-stratification.” We use these tools to re-assess a large-scale survey of voter intention in the 2016 U.S. presidential election, finding meaningful gains from the proposed methods. The approach is available in the multical R package.

Application of Attainable Region Technique to Optimize Copper Slag’s Desired Size Class

Copper slag is a hard material produced from smelting copper-bearing ores. Over the years, research has prioritized utilizing slag as a secondary source of base metals. This paper focuses on the grinding/milling of copper slag collected from the BCL Mine in Botswana to obtain a maximum amount of material in the desired size class with minimal energy consumption. This will then be followed by an integrated flotation and leaching approach of the desired size class material to recover copper. Our objectives are to determine the grinding time, ball loading, mill filling and desired size class for maximum recovery of copper mineral. The attainable region technique is an equipment-independent optimization tool employed here to determine the optimal specifications of our experimentally manipulated variables to satisfy the set objective function.

Process performance maps for membrane-based CO2 separation using artificial neural networks

Membrane-based gas separation processes are currently being implemented at different scales for several industrial applications. The optimal design of such processes, which is of key importance for their large-scale commercial deployment, has been extensively studied through parametric analyses and optimisation procedures. Nevertheless, the applicability of such design methodologies is generally limited by the large computational time and effort they require. In this work, surrogate models based on artificial neural networks are developed to circumvent the lengthy optimisation of a one-stage and two-stage cascade membrane-based gas separation process. In 200 ms, the surrogate model generates a Pareto front that describes the optimal trade-off between the process specific electricity consumption and productivity based on given input data, i.e., membrane material properties, feed composition and separation target. Whereas the surrogate model is applicable to any binary gas mixture, here its features are illustrated by creating process performance maps for post-combustion CO2 capture. Such maps provide valuable insights on: (i) attainable gas separation regions in term of CO2 recovery and CO2 purity, and (ii) the impact of membrane material, feed composition and separation target on the Pareto fronts and the optimal operating conditions.

P-graph Attainable Region Technique (PART) for Process Synthesis

P-graph Attainable Region Technique (PART) for Process Synthesis

Chemical-Phase Equilibrium of CO–CO2–H2–CH3OH–DME–H2O Mixtures in C–H–O Atom-Mol Fraction Space Using Gibbs Free Energy Minimization

This work employs Gibbs free energy minimization to carry out reaction and phase equilibrium analysis for a CO–CO2–H2–CH3OH–DME–H2O mixture, in a manner that enables a compact representation of the mixture’s feed composition in terms of the feed’s C–H–O atom-mol fractions. The concept of the Atom Species Attainable Region (ASAR) is formally defined, and propositions are developed that identify ASAR in C–H–O atom-mol fraction space for feed compositions consisting of either all six or four of the six aforementioned species. Then, Gibbs free energy minimization is carried out for a broad collection of ASAR points and a wide range of temperatures and pressures, aiming to identify conditions favoring DME production. The results of this comprehensive equilibrium analysis are then presented, and conclusions are drawn.

Prevalence of Americans reporting a family history of cancer indicative of increased cancer risk: Estimates from the 2015 National Health Interview Survey

The collection and evaluation of family health history in a clinical setting presents an opportunity to discuss cancer risk, tailor cancer screening recommendations, and identify people with an increased risk of carrying a pathogenic variant who may benefit from referral to genetic counseling and testing. National recommendations for breast and colorectal cancer screening indicate that men and women who have a first-degree relative affected with these types of cancers may benefit from talking to a healthcare provider about starting screening at an earlier age and other options for cancer prevention. The prevalence of reporting a first-degree relative who had cancer was assessed among adult respondents of the 2015 National Health Interview Survey who had never had cancer themselves (n = 27,999). We found 35.6% of adults reported having at least one first-degree relative with cancer at any site. Significant differences in reporting a family history of cancer were observed by sex, age, race/ethnicity, educational attainment, and census region. Nearly 5% of women under age 50 and 2.5% of adults under age 50 had at least one first-degree relative with breast cancer or colorectal cancer, respectively. We estimated that 5.8% of women had a family history of breast or ovarian cancer that may indicate increased genetic risk. A third of U.S. adults who have never had cancer report a family history of cancer in a first-degree relative. This finding underscores the importance of using family history to inform discussions about cancer risk and screening options between healthcare providers and their patients.

Variation in US drug overdose mortality within and between Hispanic/Latine subgroups: A disaggregation of national data

This study examined differences across Latine heritage groups (i.e., Mexican, Puerto Rican, Cuban, Dominican, Central American, South American) in rates of US drug overdose mortality.The study utilized 2015–2019 mortality data from the National Center for Health Statistics for 29,137 Hispanic individuals who died of drug overdose. We used population estimates from the American Community Survey to calculate age-standardized drug overdose mortality rates by specific Latine heritage and sex, nativity, educational attainment, and geographic region. We also calculated standardized rate ratios (SRRs), incidence rate ratios (IRRs) from negative binomial regression models, and 95% Confidence Intervals (CIs), using multiple imputation for missing Latine heritage group in select models.Drug overdose mortality rates in the Puerto Rican heritage group were more than three times as high as in the Mexican heritage group (IRR 3.61 [95% CI 3.02–4.30] in unadjusted model; IRR 3.70 [95% CI 3.31–4.15] in model adjusted for age, sex, nativity, educational attainment, and region; SRR 3.23 [95% CI, 3.15–3.32] in age-standardized model with missing Hispanic heritage imputed). Higher age-standardized rates of drug overdose mortality were observed in males than females across all Latine groups, yet the magnitude of the sex differential varied by Latine heritage. The relationship between drug overdose mortality and nativity differed by Latine heritage; in all groups except Puerto Rican, overdose mortality rates were significantly higher in the US-born than those not US-born. In contrast, overdose mortality rates were significantly lower for US-born Puerto Ricans than for Puerto Ricans who were not US-born (e.g., born in Puerto Rico; SRR, 0.84 [95% CI 0.80–0.88]). The relationship between drug overdose mortality and educational attainment (for ages 25+) also varied between Latine groups.The diverse subgroups comprising the US Latine population vary not only in rates of drug overdose mortality, but also in demographic risk factors for fatal drug overdose.

Effect of Grinding Media Size on Ferronickel Slag Ball Milling Efficiency and Energy Requirements Using Kinetics and Attainable Region Approaches

The aim of this study is to evaluate the effect that the size of grinding media exerts on ferronickel slag milling efficiency and energy savings. A series of tests were performed in a laboratory ball mill using (i) three loads of single size media, i.e., 40, 25.4, and 12.7 mm and (ii) a mixed load of balls with varying sizes. In order to simulate the industrial ball milling operation, the feed to the mill consisted of slag with natural size distribution less than 850 μm. Grinding kinetic modeling and the attainable region (AR) approach were used as tools to evaluate the data obtained during the ball milling of slag. Particular importance was given to the determination of the specific surface area of the grinding products, the identification of the grinding limit, and the maximum specific surface area which could be achieved when different grinding media sizes were used. The results showed that, in general, the breakage rates of particles obey non-first-order kinetics and coarse particles are ground more efficiently than fines. The AR approach proved that there is an optimal grinding time (or specific energy input) dependent on the ball size used for which the volume fraction of the desired size class is maximized. The use of either 25.4 mm balls or a mixed load of balls with varying sizes results in 31 and 24% decrease in energy requirements, compared to the use of balls with small size (12.7 mm).

An investigation on the breakage behavior of olivine sand particles: An attainable region technique

This study investigates the breakage behavior of olivine sand particles to identify optimal operating parameters to get products in three different define particle size classes. This was achieved by a Los Angeles abrasion test with different numbers of steel balls (up to 12), weights of steel balls (up to 0.441 kg), and different grinding durations (up to 200 mins). The data obtained were then analyzed using a model-free and equipment-independent attainable region (AR) technique. The findings revealed that the required product fineness is a function of the grinding time, numbers and weight of steel balls, and feed material size. Using 9 steel balls of 0.441 kg, a higher mass fraction of materials in the fine-sized class (−75 μm) was obtained after grinding for 200 mins. The AR technique proved to be a practical approach to optimize olivine particle size during breakage, with a potential application in sustainable soil stabilization projects.

A Review of the Milestones Reached by the Attainable Region Optimisation Technique in Particle Size Reduction

The attainable region (AR) is an optimization method adopted for use in comminution to achieve different objective functions, which all converge to optimising the production of the desired particle size distributions for downstream processes. The technique has so far mostly been used to optimise the breakage of particles in tumbling mills. It achieved the desired purpose by unveiling all possible outcomes derived from a combination of operational parameters that are bound by trajectories showing the limitations of a system. The technique has given the scientific community lenses to see the behaviour of different parameters in ball mills otherwise known as the black boxes due to their concealing nature. Since its inception, the AR technique has been applied to data obtained from the laboratory tests and simulated industrial mills and the results sometimes contradict or confirm the conventional milling practices in the industry. This makes the already conservative mining industry sceptical about its adoption. This review thus assesses the milestone covered as far as the AR development in comminution is concerned. It also helps to clarify the sources of the discrepancies between the AR results and the conventional knowledge concerning the optimisation of ball mill operational parameters.

Disparities in Reported Testing for 1p/19q Codeletion in Oligodendroglioma and Oligoastrocytoma Patients: An Analysis of the National Cancer Database.

PurposeA chromosomal 1p/19q codeletion was included as a required diagnostic component of oligodendrogliomas in the 2016 World Health Organization (WHO) classification of central nervous system tumors. We sought to evaluate disparities in reported testing for 1p/19q codeletion among oligodendroglioma and oligoastrocytoma patients before and after the guidelines.MethodsThe National Cancer Database (NCDB) was queried for patients with histologically-confirmed WHO grade II/III oligodendroglioma or oligoastrocytoma from 2011-2017. Adjusted odds of having a reported 1p/19q codeletion test for patient- and hospital-level factors were calculated before (2011-2015) and after (2017) the guidelines. The adjusted likelihood of receiving adjuvant treatment (chemotherapy and/or radiotherapy) based on reported testing was also evaluated.ResultsOverall, 6,404 patients were identified. The reported 1p/19q codeletion testing rate increased from 45.8% in 2011 to 59.8% in 2017. From 2011-2015, lack of insurance (OR 0.77; 95% CI 0.62-0.97;p=0.025), lower zip code-level educational attainment (OR 0.62; 95% CI 0.49-0.78;p<0.001), and Northeast (OR 0.68; 95% CI 0.57-0.82;p<0.001) or Southern (OR 0.62; 95% CI 0.49-0.79;p<0.001) facility geographic region were negatively associated with reported testing. In 2017, Black race (OR 0.49; 95% CI 0.26-0.91;p=0.024) and Northeast (OR 0.50; 95% CI 0.30-0.84;p=0.009) or Southern (OR 0.42; 95% CI 0.22-0.78;p=0.007) region were negatively associated with reported testing. Patients with a reported test were more likely to receive adjuvant treatment (OR 1.73; 95% CI 1.46-2.04;p<0.001).ConclusionDespite the 2016 WHO guidelines, disparities in reported 1p/19q codeletion testing by geographic region persisted while new disparities in race/ethnicity were identified, which may influence oligodendroglioma and oligoastrocytoma patient management.